Combined data display with historic data analysis

ABSTRACT

The disclosed embodiments relate to systems and methods for combining dual volatility measurements on a graphical user interface (GUI) of a computer system. The method may include receiving, via the GUI, a user selection for an anchor point, selecting a time window including the anchor point, calculating, using a volatility processor, a set of past volatility values based on the time window and the anchor point, calculating, using the volatility processor, a set of future volatility values based on the time window and the anchor point, and generating a dual volatility display for the GUI including the set of past volatility values and the set of future volatility values.

CROSS REFERENCE TO PRIOR APPLICATION

This application is a continuation under 35 U.S.C. § 120 and 37 C.F.R. §1.53(b) of U.S. patent application Ser. No. 16/577,889 filed Sep. 20,2019, which is hereby incorporated by reference in its entirety.

BACKGROUND

A financial instrument trading system, such as a futures exchange,referred to herein also as an “Exchange”, such as the Chicago MercantileExchange Inc. (CME), provides a contract market where financialproducts/instruments, for example futures and options on futures, aretraded. Futures is a term used to designate all contracts for thepurchase or sale of financial instruments or physical commodities forfuture delivery or cash settlement on a commodity futures exchange. Afutures contract is a legally binding agreement to buy or sell acommodity at a specified price at a predetermined future time, referredto as the expiration date or expiration month.

Cash Settlement is a method of settling a futures contract whereby theparty's effect final settlement when the contract expires bypaying/receiving the loss/gain related to the contract in cash, ratherthan by effecting physical sale and purchase of the underlying referencecommodity at a price determined by the futures contract price.

Typically, the exchange provides for a centralized “clearing house”through which all trades made must be confirmed, matched, and settledeach day until offset or delivered. The clearing house is an adjunct tothe exchange, and may be an operating division thereof, which isresponsible for settling trading accounts, clearing trades, collectingand maintaining performance bond funds, regulating delivery, andreporting trading data. The essential role of the clearing house is tomitigate credit risk. Clearing is the procedure through which theClearing House becomes buyer to each seller of a futures contract, andseller to each buyer, also referred to as a novation, and assumesresponsibility for protecting buyers and sellers from financial loss dueto breach of contract, by assuring performance on each contract. Aclearing member is a firm qualified to clear trades through the ClearingHouse.

Current financial instrument trading systems allow customers to submitorders and receive confirmations, market data, and other informationelectronically via a network. These “electronic” marketplaces havelargely supplanted the pit based trading systems whereby the traders, ortheir representatives, all physically stand in a designated location,i.e. a trading pit, and trade with each other via oral and hand basedcommunication. In contrast to the pit based trading system wherelike-minded buyers and sellers can readily find each other to trade,electronic marketplaces must electronically “match” the orders placed bybuyers and sellers on behalf thereof. Electronic trading systems mayoffer a more efficient and transparent system of trading. Electronictrading systems may achieve more fair and equitable matching amongtraders as well as identify more opportunities to trade, therebyimproving market liquidity.

In the technological field of computer science, systems are designed toprovide efficient and quick calculations of market conditions. Oneexample market condition is volatility. Volatility measures the changesof a value over time. For example, the volatility of a financialinstrument over time may be used to analyze the performance of thefinancial instruments as well as correlation for margin requirements.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an illustrative computer network system that may be usedto implement aspects of the disclosed embodiments.

FIG. 2 depicts an illustrative embodiment of a general computer systemfor use with the disclosed embodiments.

FIG. 3 depicts a flow chart showing exemplary operation of the system ofFIGS. 1 and 2.

FIG. 4 depicts an example graphical user interface (GUI) for dualvolatility calculations of one or more financial instruments accordingto an anchor.

FIG. 5 depicts another example GUI for dual volatility calculationsincluding forward volatility.

FIG. 6 depicts another example GUI for dual volatility calculationsincluding a dynamic matrix.

FIG. 7 depicts another example GUI for dual volatility calculationsincluding multiple anchors.

FIG. 8 depicts another example GUI for dual volatility calculationsincluding a frequency selector.

DETAILED DESCRIPTION

Volatility is a calculation of the variation of a quantity over time.For financial instruments, the quantity may be price. Various formulaeor techniques are possible for the calculation of volatility. Oneexample is the standard deviation of the logarithmic change of thequantity. The logarithm change of the quantity may be the natural log ofthe ratio of the final value to the initial value. Equation 1 summariesthese calculations for a single interval using a final price P_(f) and aprice P_(i):

$\begin{matrix}{{Volatility} = \sqrt{\ln\frac{P_{f}}{P_{i}}}} & {{Eq}.\mspace{11mu} 1}\end{matrix}$

Realized, or Historical Volatility may be calculated numerically basedon the standard deviation of the square root of the variance in price.Equation 2 provides a root-mean-squared form for historical or realizedvolatility according to the ratio of a current price to a previousprice. For multiple quantities over time (e.g., 252 trading days peryear), volatility is calculated according to Equation 2 as the summationof the individual interval changes in the quantities according to afirst price P_(t) and a second or previous price P_(t-1):

$\begin{matrix}{{Volatility} = {100 \times \sqrt{\frac{\left. {252 \times {\sum\limits_{t = 1}^{n}\left( {\ln\left( \frac{P_{t}}{P_{t - 1}} \right)} \right)^{2}}} \right)}{n}}}} & {{Eq}.\mspace{11mu} 2}\end{matrix}$

Historical volatility (realized volatility) may be calculated accordingto any of these techniques. Historical volatility of a financialinstrument may be based on a series of past market prices. Historicalvolatility describes what happened in the past.

Implied volatility, the market's estimate of future realized volatility,is calculated from quoted options prices in the market. To deriveimplied volatilities, practitioners utilize an options pricing model,such as the Black-Scholes-Merton formula. One example, as provided byEquation 3 defines option price according to volatility or sigma (a)according to the option price, the risk free interest rate (r), theunderlying asset price (S) (e.g., stock price or futures price), and thechange of the option price with respect to time (dV/dt) such that Vrepresents the price of the option as a function of underlying price (S)and time (t).

$\begin{matrix}{{{Option}\mspace{14mu}{Price}} = {\frac{\partial V}{\partial t} + {\frac{1}{2}\sigma^{2}S^{2}\frac{\partial^{2}V}{\partial S^{2}}} + {rS\frac{\partial V}{\partial S}}}} & {{Eq}.\mspace{11mu} 3}\end{matrix}$

In practice, practitioners may reverse the calculation and solve for thevolatility term (a) from the market's quoted price. Implied volatilitiesfor non-observable strike prices or expirations, or forward dates, canthen be implied or predicted based on the implied volatilities ofoptions already calculated. Especially in options markets, analysisfocuses on volatility and the distribution of prices, rather than thedirection or trend of increasing or decreasing prices. Using Equation 3,the σ² term may be algorithmically swapped with the option price. Theoption price being the known quantity and the σ² value being the unknownquantity, which is then solved for.

Different options contracts for the same underlying asset may havedifferent expiration dates. The prices of these options for the variousexpiration dates describe the markets perception for the futurevolatility of the underlying for the options. Thus, options can providean estimate of where prices are predicted to go in the future. Moreinformation is provided by the shape of the volatility term structure.Even more information is provided by the forward implied volatility thatgovern market implication of specified periods of time. One examplecalculation for implied volatility is described by the Black-Scholesmodel.

An analogy is that the past (realized or historical volatility) is likelooking in the rear-view mirror, while the implied volatility termstructure presents the market's estimates of future volatility, which islike driving looking straight ahead through the windshield. Thefollowing embodiments solve technical challenges faced in the displayand coordination of historical volatility and implied volatility. Thesechallenges are rooted in the differences in calculation techniques forhistorical volatility and implied volatility. The following embodimentsprovide more information/data on a single view and unique controlstructures to control the time display. The historical volatility andimplied volatility are coordinated to provide a seamless view of bothpast and future volatility. The combination of historical and impliedvolatility offers a significantly improved view of the optionsmarketplace (past plus future expected) volatility dynamics. Further,the baseline implementation allows additional user selections to pivotthe combined view according to an anchor date, which dynamically adjuststhe calculations of volatility in real time under the control of theuser.

Exchange Computing System

The disclosed embodiments may be implemented in a data transactionprocessing system that processes data items or objects. Customer or userdevices (e.g., client computers) may submit electronic data transactionrequest messages, e.g., inbound messages, to the data transactionprocessing system over a data communication network. The electronic datatransaction request messages may include, for example, transactionmatching parameters, such as instructions and/or values, for processingthe data transaction request messages within the data transactionprocessing system. The instructions may be to perform transactions,e.g., buy or sell a quantity of a product at a range of values definedequations. Products, e.g., financial instruments, or order booksrepresenting the state of an electronic marketplace for a product, maybe represented as data objects within the exchange computing system. Theinstructions may also be conditional, e.g., buy or sell a quantity of aproduct at a given value if a trade for the product is executed at someother reference value. The data transaction processing system mayinclude various specifically configured matching processors that match,e.g., automatically, electronic data transaction request messages forthe same one of the data items or objects. The specifically configuredmatching processors may match, or attempt to match, electronic datatransaction request messages based on multiple transaction matchingparameters from the different client computers. The specificallyconfigured matching processors may additionally generate informationindicative of a state of an environment (e.g., the state of the orderbook) based on the processing, and report this information to datarecipient computing systems via outbound messages published via one ormore data feeds.

For example, one exemplary environment where the disclosed embodimentsmay be desirable is in financial markets, and in particular, electronicfinancial exchanges, such as a futures exchange, such as the ChicagoMercantile Exchange Inc. (CME).

A financial instrument trading system, such as a futures exchange, suchas the Chicago Mercantile Exchange Inc. (CME), provides a contractmarket where financial instruments, e.g., futures and options onfutures, are traded using electronic systems. “Futures” is a term usedto designate all contracts for the purchase or sale of financialinstruments or physical commodities for future delivery or cashsettlement on a commodity futures exchange. A futures contract is alegally binding agreement to buy or sell a commodity at a specifiedprice at a predetermined future time. An option contract is the right,but not the obligation, to sell or buy the underlying instrument (inthis case, a futures contract) at a specified price on or before acertain expiration date. An option contract offers an opportunity totake advantage of futures price moves without actually having a futuresposition. The commodity to be delivered in fulfillment of the contract,or alternatively the commodity for which the cash market price shalldetermine the final settlement price of the futures contract, is knownas the contract's underlying reference or “underlier.” The underlying orunderlier for an options contract is the corresponding futures contractthat is purchased or sold upon the exercise of the option.

The terms and conditions of each futures contract are standardized as tothe specification of the contract's underlying reference commodity, thequality of such commodity, quantity, delivery date, and means ofcontract settlement. Cash settlement is a method of settling a futurescontract whereby the parties effect final settlement when the contractexpires by paying/receiving the loss/gain related to the contract incash, rather than by effecting physical sale and purchase of theunderlying reference commodity at a price determined by the futurescontract price. Options and futures may be based on more generalizedmarket indicators, such as stock indices, interest rates, futurescontracts and other derivatives.

An exchange may provide for a centralized “clearing house” through whichtrades made must be confirmed, matched, and settled each day untiloffset or delivered. The clearing house may be an adjunct to anexchange, and may be an operating division of an exchange, which isresponsible for settling trading accounts, clearing trades, collectingand maintaining performance bond funds, regulating delivery, andreporting trading data. One of the roles of the clearing house is tomitigate credit risk. Clearing is the procedure through which theclearing house becomes buyer to each seller of a futures contract, andseller to each buyer, also referred to as a novation, and assumesresponsibility for protecting buyers and sellers from financial loss dueto breach of contract, by assuring performance on each contract. Aclearing member is a firm qualified to clear trades through the clearinghouse.

An exchange computing system may operate under a central counterpartymodel, where the exchange acts as an intermediary between marketparticipants for the transaction of financial instruments. Inparticular, the exchange computing system novates itself into thetransactions between the market participants, i.e., splits a giventransaction between the parties into two separate transactions where theexchange computing system substitutes itself as the counterparty to eachof the parties for that part of the transaction, sometimes referred toas a novation. In this way, the exchange computing system acts as aguarantor and central counterparty and there is no need for the marketparticipants to disclose their identities to each other, or subjectthemselves to credit or other investigations by a potentialcounterparty. For example, the exchange computing system insulates onemarket participant from the default by another market participant.Market participants need only meet the requirements of the exchangecomputing system. Anonymity among the market participants encourages amore liquid market environment as there are lower barriers toparticipation. The exchange computing system can accordingly offerbenefits such as centralized and anonymous matching and clearing.

Electronic Data Transaction Request Messages

As used herein, a financial message, or an electronic message, refersboth to messages communicated by market participants to an electronictrading or market system and vice versa. The messages may becommunicated using packeting or other techniques operable to communicateinformation between systems and system components. Some messages may beassociated with actions to be taken in the electronic trading or marketsystem. In particular, in one embodiment, upon receipt of a request, atoken is allocated and included in a TCP shallow acknowledgmenttransmission sent back to the participant acknowledging receipt of therequest. It should be appreciated that while this shallow acknowledgmentis, in some sense, a response to the request, it does not confirm theprocessing of an order included in the request. The participant, i.e.,their device, then sends back a TCP acknowledgment which acknowledgesreceipt of the shallow acknowledgment and token.

Financial messages communicated to the electronic trading system, alsoreferred to as “inbound” messages, may include associated actions thatcharacterize the messages, such as trader orders, order modifications,order cancellations and the like, as well as other message types.Inbound messages may be sent from client devices associated with marketparticipants, or their representatives, e.g., trade order messages,etc., to an electronic trading or market system. For example, a marketparticipant may submit an electronic message to the electronic tradingsystem that includes an associated specific action to be undertaken bythe electronic trading system, such as entering a new trade order intothe market or modifying an existing order in the market. In oneembodiment, if a participant wishes to modify a previously sent request,e.g., a prior order which has not yet been processed or traded, they maysend a request message comprising a request to modify the prior request.In one exemplary embodiment, the incoming request itself, e.g., theinbound order entry, may be referred to as an iLink message. iLink is abidirectional communications/message protocol/message format implementedby the Chicago Mercantile Exchange Inc.

Financial messages communicated from the electronic trading system,referred to as “outbound” messages, may include messages responsive toinbound messages, such as confirmation messages, or other messages suchas market update messages, quote messages, and the like. Outboundmessages may be disseminated via data feeds.

Financial messages may further be categorized as having or reflecting animpact on a market or electronic marketplace, also referred to as an“order book” or “book,” for a traded product, such as a prevailing pricetherefore, number of resting orders at various price levels andquantities thereof, etc., or not having or reflecting an impact on amarket or a subset or portion thereof. In one embodiment, an electronicorder book may be understood to be an electronic collection of theoutstanding or resting orders for a financial instrument.

For example, a request to place a trade may result in a responseindicative of the trade either being matched with, or being rested on anorder book to await, a suitable counter-order. This response may includea message directed solely to the trader who submitted the order toacknowledge receipt of the order and report whether it was matched, andthe extent thereto, or rested. The response may further include amessage to all market participants reporting a change in the order bookdue to the order. This response may take the form of a report of thespecific change to the order book, e.g., an order for quantity X atprice Y was added to the book (referred to, in one embodiment, as aMarket By Order message), or may simply report the result, e.g., pricelevel Y now has orders for a total quantity of Z (where Z is the sum ofthe previous resting quantity plus quantity X of the new order). In somecases, requests may elicit a non-impacting response, such as temporallyproximate to the receipt of the request, and then cause a separatemarket-impact reflecting response at a later time. For example, a stoporder, fill or kill order (FOK), also known as an immediate or cancelorder, or other conditional request may not have an immediate marketimpacting effect, if at all, until the requisite conditions are met.

An acknowledgement or confirmation of receipt, e.g., a non-marketimpacting communication, may be sent to the trader simply confirmingthat the order was received. Upon the conditions being met and a marketimpacting result thereof occurring, a market-impacting message may betransmitted as described herein both directly back to the submittingmarket participant and to all market participants (in a Market By Price“MBP” e.g., Aggregated By Value (“ABV”) book, or Market By Order “MBO”,e.g., Per Order (“PO”) book format). It should be appreciated thatadditional conditions may be specified, such as a time or price limit,which may cause the order to be dropped or otherwise canceled and thatsuch an event may result in another non-market-impacting communicationinstead. In some implementations, market impacting communications may becommunicated separately from non-market impacting communications, suchas via a separate communications channel or feed.

It should be further appreciated that various types of market data feedsmay be provided which reflect different markets or aspects thereof.Market participants may then, for example, subscribe to receive thosefeeds of interest to them. For example, data recipient computing systemsmay choose to receive one or more different feeds. As market impactingcommunications usually tend to be more important to market participantsthan non-impacting communications, this separation may reduce congestionand/or noise among those communications having or reflecting an impacton a market or portion thereof. Furthermore, a particular market datafeed may only communicate information related to the top buy/sell pricesfor a particular product, referred to as “top of book” feed, e.g., onlychanges to the top 10 price levels are communicated. Such limitationsmay be implemented to reduce consumption of bandwidth and messagegeneration resources. In this case, while a request message may beconsidered market-impacting if it affects a price level other than thetop buy/sell prices, it will not result in a message being sent to themarket participants.

Examples of the various types of market data feeds which may be providedby electronic trading systems, such as the CME, in order to providedifferent types or subsets of market information or to provide suchinformation in different formats include Market By Order or Per Order,Market Depth (also known as Market by Price or Aggregated By Value to adesignated depth of the book), e.g., CME offers a 10-deep market byprice feed, Top of Book (a single depth Market by Price feed), andcombinations thereof. There may also be all manner of specialized feedsin terms of the content, i.e., providing, for example, derived data,such as a calculated index.

Market data feeds may be characterized as providing a “view” or“overview” of a given market, an aggregation or a portion thereof orchanges thereto. For example, a market data feed, such as a Market ByPrice (“MBP”) feed, also known as an Aggregated By Value (“ABV”) feed,may convey, with each message, the entire/current state of a market, orportion thereof, for a particular product as a result of one or moremarket impacting events. For example, an MBP message may convey a totalquantity of resting buy/sell orders at a particular price level inresponse to a new order being placed at that price. An MBP message mayconvey a quantity of an instrument which was traded in response to anincoming order being matched with one or more resting orders. MBPmessages may only be generated for events affecting a portion of amarket, e.g., only the top 10 resting buy/sell orders and, thereby, onlyprovide a view of that portion. As used herein, a market impactingrequest may be said to impact the “view” of the market as presented viathe market data feed.

An MBP feed may utilize different message formats for conveyingdifferent types of market impacting events. For example, when a neworder is rested on the order book, an MBP message may reflect thecurrent state of the price level to which the order was added, e.g., thenew aggregate quantity and the new aggregate number of resting orders.As can be seen, such a message conveys no information about theindividual resting orders, including the newly rested order, themselvesto the market participants. Only the submitting market participant, whoreceives a separate private message acknowledging the event, knows thatit was their order that was added to the book. Similarly, when a tradeoccurs, an MBP message may be sent which conveys the price at which theinstrument was traded, the quantity traded and the number ofparticipating orders, but may convey no information as to whoseparticular orders contributed to the trade. MBP feeds may further batchreporting of multiple events, i.e., report the result of multiple marketimpacting events in a single message.

Alternatively, a market data feed, referred to as a Market By Order(“MBO”) feed also known as a Per Order (“PO”) feed, may convey datareflecting a change that occurred to the order book rather than theresult of that change, e.g., that order ABC for quantity X was added toprice level Y or that order ABC and order XYZ traded a quantity X at aprice Y. In this case, the MBO message identifies only the change thatoccurred so a market participant wishing to know the current state ofthe order book must maintain their own copy and apply the changereflected in the message to know the current state. As can be seen,MBO/PO messages may carry much more data than MBP/ABV messages becauseMBO/PO messages reflect information about each order, whereas MBP/ABVmessages contain information about orders affecting some predeterminedvalue levels. Furthermore, because specific orders, but not thesubmitting traders thereof, are identified, other market participantsmay be able to follow that order as it progresses through the market,e.g., as it is modified, canceled, traded, etc.

An ABV book data object may include information about multiple values.The ABV book data object may be arranged and structured so thatinformation about each value is aggregated together. Thus, for a givenvalue V, the ABV book data object may aggregate all the information byvalue, such as for example, the number of orders having a certainposition at value V, the quantity of total orders resting at value V,etc. Thus, the value field may be the key, or may be a unique field,within an ABV book data object. In one embodiment, the value for eachentry within the ABV book data object is different. In one embodiment,information in an ABV book data object is presented in a manner suchthat the value field is the most granular field of information.

A PO book data object may include information about multiple orders. ThePO book data object may be arranged and structured so that informationabout each order is represented. Thus, for a given order O, the PO bookdata object may provide all of the information for order O. Thus, theorder field may be the key, or may be a unique field, within a PO bookdata object. In one embodiment, the order ID for each entry within thePO book data object is different. In one embodiment, information in a PObook data object is presented in a manner such that the order field isthe most granular field of information.

Thus, the PO book data object may include data about unique orders,e.g., all unique resting orders for a product, and the ABV book dataobject may include data about unique values, e.g., up to a predeterminedlevel, e.g., top ten price or value levels, for a product.

A market data feed may also provide information about volatility. Themarket data feed may include data supporting a single volatility indexfor combining dual volatility calculations for both historicalvolatility and implied volatility.

It should be appreciated that the number, type and manner of market datafeeds provided by an electronic trading system are implementationdependent and may vary depending upon the types of products traded bythe electronic trading system, customer/trader preferences, bandwidthand data processing limitations, etc. and that all such feeds, nowavailable or later developed, are contemplated herein. MBP/ABV andMBO/PO feeds may refer to categories/variations of market data feeds,distinguished by whether they provide an indication of the current stateof a market resulting from a market impacting event (MBP) or anindication of the change in the current state of a market due to amarket impacting event (MBO).

Messages, whether MBO or MBP, generated responsive to market impactingevents which are caused by a single order, such as a new order, an ordercancellation, an order modification, etc., are fairly simple and compactand easily created and transmitted. However, messages, whether MBO orMBP, generated responsive to market impacting events which are caused bymore than one order, such as a trade, may require the transmission of asignificant amount of data to convey the requisite information to themarket participants. For trades involving a large number of orders,e.g., a buy order for a quantity of 5000 which matches 5000 sell orderseach for a quantity of 1, a significant amount of information may needto be sent, e.g., data indicative of each of the 5000 trades that haveparticipated in the market impacting event.

In one embodiment, an exchange computing system may generate multipleorder book objects, one for each type of view that is published orprovided. For example, the system may generate a PO book object and anABV book object. It should be appreciated that each book object, or viewfor a product or market, may be derived from the Per Order book object,which includes all the orders for a given financial product or market.

An inbound message may include an order that affects the PO book object,the ABV book object, or both. An outbound message may include data fromone or more of the structures within the exchange computing system,e.g., the PO book object queues or the ABV book object queues.

Furthermore, each participating trader needs to receive a notificationthat their particular order has traded. Continuing with the example,this may require sending 5001 individual trade notification messages, oreven 10,000+ messages where each contributing side (buy vs. sell) isseparately reported, in addition to the notification sent to all of themarket participants.

As detailed in U.S. Patent Publication No. 2015/0161727, the entirety ofwhich is incorporated by reference herein and relied upon, it may berecognized that trade notifications sent to all market participants mayinclude redundant information repeated for each participating trade anda structure of an MBP trade notification message may be provided whichresults in a more efficient communication of the occurrence of a trade.The message structure may include a header portion which indicates thetype of transaction which occurred, i.e., a trade, as well as othergeneral information about the event, an instrument portion whichcomprises data about each instrument which was traded as part of thetransaction, and an order portion which comprises data about eachparticipating order. In one embodiment, the header portion may include amessage type, Transaction Time, Match Event Indicator, and Number ofMarket Data Entries (“No. MD Entries”) fields. The instrument portionmay include a market data update action indicator (“MD Update Action”),an indication of the Market Data Entry Type (“MD Entry Type”), anidentifier of the instrument/security involved in the transaction(“Security ID”), a report sequence indicator (“Rpt Seq”), the price atwhich the instrument was traded (“MD Entry PX”), the aggregate quantitytraded at the indicated price (“ConsTradeQty”), the number ofparticipating orders (“NumberOfOrders”), and an identifier of theaggressor side (“Aggressor Side”) fields. The order portion may furtherinclude an identifier of the participating order (“Order ID”), describedin more detail below, and the quantity of the order traded (“MD EntrySize”) fields. It should be appreciated that the particular fieldsincluded in each portion are implementation dependent and that differentfields in addition to, or in lieu of, those listed may be includeddepending upon the implementation. It should be appreciated that theexemplary fields can be compliant with the FIX binary and/or FIX/FASTprotocol for the communication of the financial information.

The instrument portion contains a set of fields, e.g., seven fieldsaccounting for 23 bytes, which are repeated for each participatinginstrument. In complex trades, such as trades involving combinationorders or strategies, e.g., spreads, or implied trades, there may bemultiple instruments being exchanged among the parties. In oneembodiment, the order portion includes only one field, accounting for 4bytes, for each participating order which indicates the quantity of thatorder which was traded. As will be discussed below, the order portionmay further include an identifier of each order, accounting for anadditional 8 bytes, in addition to the quantity thereof traded. Asshould be appreciated, data which would have been repeated for eachparticipating order, is consolidated or otherwise summarized in theheader and instrument portions of the message thereby eliminatingredundant information and, overall, significantly reducing the size ofthe message.

While the disclosed embodiments may be discussed with respect to an MBPmarket data feed, it should be appreciated that the disclosedembodiments may also be applicable to an MBO market data feed.

Market Segment Gateway

In one embodiment, the disclosed system may include a Market SegmentGateway (“MSG”) that is the point of ingress/entry and/oregress/departure for all transactions, i.e., the network traffic/packetscontaining the data therefore, specific to a single market at which theorder of receipt of those transactions may be ascribed. An MSG or MarketSegment Gateway may be utilized for the purpose of deterministicoperation of the market. The electronic trading system may includemultiple markets, and because the electronic trading system includes oneMSG for each market/product implemented thereby, the electronic tradingsystem may include multiple MSGs. For more detail on deterministicoperation in a trading system, see U.S. Patent Publication No.2015/0127513 entitled “Transactionally Deterministic High SpeedFinancial Exchange Having Improved, Efficiency, Communication,Customization, Performance, Access, Trading Opportunities, CreditControls, And Fault Tolerance” and filed on Nov. 7, 2013 (“the '513Publication”), the entire disclosure of which is incorporated byreference herein and relied upon.

For example, a participant may send a request for a new transaction,e.g., a request for a new order, to the MSG. The MSG extracts or decodesthe request message and determines the characteristics of the requestmessage.

The MSG may include, or otherwise be coupled with, a buffer, cache,memory, database, content addressable memory, data store or other datastorage mechanism, or combinations thereof, which stores data indicativeof the characteristics of the request message. The request is passed tothe transaction processing system, e.g., the match engine.

An MSG or Market Segment Gateway may be utilized for the purpose ofdeterministic operation of the market. Transactions for a particularmarket may be ultimately received at the electronic trading system viaone or more points of entry, e.g., one or more communicationsinterfaces, at which the disclosed embodiments apply determinism, whichas described may be at the point where matching occurs, e.g., at eachmatch engine (where there may be multiple match engines, each for agiven product/market, or moved away from the point where matching occursand closer to the point where the electronic trading system firstbecomes “aware” of the incoming transaction, such as the point wheretransaction messages, e.g., orders, ingress the electronic tradingsystem. Generally, the terms “determinism” or “transactionaldeterminism” may refer to the processing, or the appearance thereof, oforders in accordance with defined business rules. Accordingly, as usedherein, the point of determinism may be the point at which theelectronic trading system ascribes an ordering to incomingtransactions/orders relative to other incoming transactions/orders suchthat the ordering may be factored into the subsequent processing, e.g.,matching, of those transactions/orders as will be described. For moredetail on deterministic operation in a trading system, see the '513Publication.

Electronic Trading

Electronic trading of financial instruments, such as futures contracts,is conducted by market participants sending orders, such as to buy orsell one or more futures contracts, in electronic form to the exchange.These electronically submitted orders to buy and sell are then matched,if possible, by the exchange, i.e., by the exchange's matching engine,to execute a trade. Outstanding (unmatched, wholly unsatisfied/unfilledor partially satisfied/filled) orders are maintained in one or more datastructures or databases referred to as “order books,” such orders beingreferred to as “resting,” and made visible, i.e., their availability fortrading is advertised, to the market participants through electronicnotifications/broadcasts, referred to as market data feeds. An orderbook is typically maintained for each product, e.g., instrument, tradedon the electronic trading system and generally defines or otherwiserepresents the state of the market for that product, i.e., the currentprices at which the market participants are willing to buy or sell thatproduct. As such, as used herein, an order book for a product may alsobe referred to as a market for that product.

Upon receipt of an incoming order to trade in a particular financialinstrument, whether for a single-component financial instrument, e.g., asingle futures contract, or for a multiple-component financialinstrument, e.g., a combination contract such as a spread contract, amatch engine, as described herein, will attempt to identify a previouslyreceived but unsatisfied order counter thereto, i.e., for the oppositetransaction (buy or sell) in the same financial instrument at the sameor better price (but not necessarily for the same quantity unless, forexample, either order specifies a condition that it must be entirelyfilled or not at all).

Previously received but unsatisfied orders, i.e., orders which eitherdid not match with a counter order when they were received or theirquantity was only partially satisfied, referred to as a partial fill,are maintained by the electronic trading system in an order bookdatabase/data structure to await the subsequent arrival of matchingorders or the occurrence of other conditions which may cause the orderto be modified or otherwise removed from the order book.

If the match engine identifies one or more suitable previously receivedbut unsatisfied counter orders, they, and the incoming order, arematched to execute a trade there between to at least partially satisfythe quantities of one or both the incoming order or the identifiedorders. If there remains any residual unsatisfied quantity of theidentified one or more orders, those orders are left on the order bookwith their remaining quantity to await a subsequent suitable counterorder, i.e., to rest. If the match engine does not identify a suitablepreviously received but unsatisfied counter order, or the one or moreidentified suitable previously received but unsatisfied counter ordersare for a lesser quantity than the incoming order, the incoming order isplaced on the order book, referred to as “resting”, with original orremaining unsatisfied quantity, to await a subsequently receivedsuitable order counter thereto. The match engine then generates matchevent data reflecting the result of this matching process. Othercomponents of the electronic trading system, as will be described, thengenerate the respective order acknowledgment and market data messagesand transmit those messages to the market participants.

Matching, which is a function typically performed by the exchange, is aprocess, for a given order which specifies a desire to buy or sell aquantity of a particular instrument at a particular price, ofseeking/identifying one or more wholly or partially, with respect toquantity, satisfying counter orders thereto, e.g., a sell counter to anorder to buy, or vice versa, for the same instrument at the same, orsometimes better, price (but not necessarily the same quantity), whichare then paired for execution to complete a trade between the respectivemarket participants (via the exchange) and at least partially satisfythe desired quantity of one or both of the order and/or the counterorder, with any residual unsatisfied quantity left to await anothersuitable counter order, referred to as “resting.” A match event mayoccur, for example, when an aggressing order matches with a restingorder. In one embodiment, two orders match because one order includesinstructions for or specifies buying a quantity of a particularinstrument at a particular price, and the other order includesinstructions for or specifies selling a (different or same) quantity ofthe instrument at a same or better price. It should be appreciated thatperforming an instruction associated with a message may includeattempting to perform the instruction. Whether or not an exchangecomputing system is able to successfully perform an instruction maydepend on the state of the electronic marketplace.

While the disclosed embodiments will be described with respect to aproduct by product or market by market implementation, e.g. implementedfor each market/order book, it will be appreciated that the disclosedembodiments may be implemented so as to apply across markets formultiple products traded on one or more electronic trading systems, suchas by monitoring an aggregate, correlated or other derivation of therelevant indicative parameters as described herein.

While the disclosed embodiments may be discussed in relation to futuresand/or options on futures trading, it should be appreciated that thedisclosed embodiments may be applicable to any equity, fixed incomesecurity, currency, commodity, options or futures trading system ormarket now available or later developed. It may be appreciated that atrading environment, such as a futures exchange as described herein,implements one or more economic markets where rights and obligations maybe traded. As such, a trading environment may be characterized by a needto maintain market integrity, transparency, predictability,fair/equitable access and participant expectations with respect thereto.In addition, it may be appreciated that electronic trading systemsfurther impose additional expectations and demands by marketparticipants as to transaction processing speed, latency, capacity andresponse time, while creating additional complexities relating thereto.Accordingly, as will be described, the disclosed embodiments may furtherinclude functionality to ensure that the expectations of marketparticipants are met, e.g., that transactional integrity and predictablesystem responses are maintained.

Financial instrument trading systems allow traders to submit orders andreceive confirmations, market data, and other information electronicallyvia electronic messages exchanged using a network. Electronic tradingsystems ideally attempt to offer a more efficient, fair and balancedmarket where market prices reflect a true consensus of the value oftraded products among the market participants, where the intentional orunintentional influence of any one market participant is minimized ifnot eliminated, and where unfair or inequitable advantages with respectto information access are minimized if not eliminated.

Electronic marketplaces attempt to achieve these goals by usingelectronic messages to communicate actions and related data of theelectronic marketplace between market participants, clearing firms,clearing houses, and other parties. The messages can be received usingan electronic trading system, wherein an action or transactionassociated with the messages may be executed. For example, the messagemay contain information relating to an order to buy or sell a product ina particular electronic marketplace, and the action associated with themessage may indicate that the order is to be placed in the electronicmarketplace such that other orders which were previously placed maypotentially be matched to the order of the received message. Thus, theelectronic marketplace may conduct market activities through electronicsystems. CLEARING HOUSE

The clearing house of an exchange clears, settles and guarantees matchedtransactions in contracts occurring through the facilities of theexchange. In addition, the clearing house establishes and monitorsfinancial requirements for clearing members and conveys certain clearingprivileges in conjunction with the relevant exchange markets.

The clearing house establishes clearing level performance bonds(margins) for all products of the exchange and establishes minimumperformance bond requirements for customers of such products. Aperformance bond, also referred to as a margin requirement, correspondswith the funds that must be deposited by a customer with his or herbroker, by a broker with a clearing member or by a clearing member withthe clearing house, for the purpose of insuring the broker or clearinghouse against loss on open futures or options contracts. This is not apart payment on a purchase. The performance bond helps to ensure thefinancial integrity of brokers, clearing members and the exchange as awhole. The performance bond refers to the minimum dollar depositrequired by the clearing house from clearing members in accordance withtheir positions. Maintenance, or maintenance margin, refers to a sum,usually smaller than the initial performance bond, which must remain ondeposit in the customer's account for any position at all times. Theinitial margin is the total amount of margin per contract required bythe broker when a futures position is opened. A drop in funds below thislevel requires a deposit back to the initial margin levels, i.e., aperformance bond call. If a customer's equity in any futures positiondrops to or under the maintenance level because of adverse price action,the broker must issue a performance bond/margin call to restore thecustomer's equity. A performance bond call, also referred to as a margincall, is a demand for additional funds to bring the customer's accountback up to the initial performance bond level whenever adverse pricemovements cause the account to go below the maintenance.

The exchange derives its financial stability in large part by removingdebt obligations among market participants as they occur. This isaccomplished by determining a settlement price at the close of themarket each day for each contract and marking all open positions to thatprice, referred to as “mark to market.” Every contract is debited orcredited based on that trading session's gains or losses. As prices movefor or against a position, funds flow into and out of the tradingaccount. In the case of the CME, each business day by 6:40 a.m. Chicagotime, based on the mark-to-the-market of all open positions to theprevious trading day's settlement price, the clearing house pays to orcollects cash from each clearing member. This cash flow, known assettlement variation, is performed by CME's settlement banks based oninstructions issued by the clearing house. All payments to andcollections from clearing members are made in “same-day” funds. Inaddition to the 6:40 a.m. settlement, a daily intra-day mark-to-themarket of all open positions, including trades executed during theovernight GLOBEX®, the CME's electronic trading systems, trading sessionand the current day's trades matched before 11:15 a.m., is performedusing current prices. The resulting cash payments are made intra-day forsame day value. In times of extreme price volatility, the clearing househas the authority to perform additional intra-day mark-to-the-marketcalculations on open positions and to call for immediate payment ofsettlement variation. CME's mark-to-the-market settlement system differsfrom the settlement systems implemented by many other financial markets,including the interbank, Treasury securities, over-the-counter foreignexchange and debt, options, and equities markets, where participantsregularly assume credit exposure to each other. In those markets, thefailure of one participant can have a ripple effect on the solvency ofthe other participants. Conversely, CME's mark-to-the-market system doesnot allow losses to accumulate over time or allow a market participantthe opportunity to defer losses associated with market positions.

While the disclosed embodiments may be described in reference to theCME, it should be appreciated that these embodiments are applicable toany exchange. Such other exchanges may include a clearing house that,like the CME clearing house, clears, settles and guarantees all matchedtransactions in contracts of the exchange occurring through itsfacilities. In addition, such clearing houses establish and monitorfinancial requirements for clearing members and convey certain clearingprivileges in conjunction with the relevant exchange markets.

The disclosed embodiments are also not limited to uses by a clearinghouse or exchange for purposes of enforcing a performance bond or marginrequirement. For example, a market participant may use the disclosedembodiments in a simulation or other analysis of a portfolio. In suchcases, the settlement price may be useful as an indication of a value atrisk and/or cash flow obligation rather than a performance bond. Thedisclosed embodiments may also be used by market participants or otherentities to forecast or predict the effects of a prospective position onthe margin requirement of the market participant.

Trading Environment

The embodiments may be described in terms of a distributed computingsystem. The particular examples identify a specific set of componentsuseful in a futures and options exchange. However, many of thecomponents and inventive features are readily adapted to otherelectronic trading environments. The specific examples described hereinmay teach specific protocols and/or interfaces, although it should beunderstood that the principals involved may be extended to, or appliedin, other protocols and interfaces.

It should be appreciated that the plurality of entities utilizing orinvolved with the disclosed embodiments, e.g., the market participants,may be referred to by other nomenclature reflecting the role that theparticular entity is performing with respect to the disclosedembodiments and that a given entity may perform more than one roledepending upon the implementation and the nature of the particulartransaction being undertaken, as well as the entity's contractual and/orlegal relationship with another market participant and/or the exchange.

An exemplary trading network environment for implementing tradingsystems and methods is shown in FIG. 1. The computer system of FIG. 1includes an Exchange Computer System 100 receives messages that includeorders and transmits market data related to orders and trades to users,such as via wide area network 126 and/or local area network 124 andcomputer devices 114, 116, 118, 120 and 122, as will be described below,coupled with the Exchange Computer System 100.

Herein, the phrase “coupled with” is defined to mean directly connectedto or indirectly connected through one or more intermediate components.Such intermediate components may include both hardware- andsoftware-based components. Further, to clarify the use in the pendingclaims and to hereby provide notice to the public, the phrases “at leastone of <A>, <B>, . . . and <N>” or “at least one of <A>, <B>, . . . <N>,or combinations thereof” are defined by the Applicant in the broadestsense, superseding any other implied definitions hereinbefore orhereinafter unless expressly asserted by the Applicant to the contrary,to mean one or more elements selected from the group comprising A, B, .. . and N, that is to say, any combination of one or more of theelements A, B, . . . or N including any one element alone or incombination with one or more of the other elements which may alsoinclude, in combination, additional elements not listed.

The Exchange Computer System 100 may be implemented with one or moremainframe, desktop or other computers, such as the example computer 200described herein with respect to FIG. 2. A user database 102 may beprovided which includes information identifying traders and other usersof Exchange Computer System 100, such as account numbers or identifiers,usernames, and passwords. An account data module 104 may be providedwhich may process account information that may be used during trades.

A match engine module 106 may be included to match bid and offer pricesand may be implemented with software that executes one or morealgorithms for matching bids and offers. A trade database 108 may beincluded to store information identifying trades and descriptions oftrades. In particular, a trade database may store informationidentifying the time that a trade took place and the contract price. Anorder book module 110 may be included to compute or otherwise determinecurrent bid and offer prices, e.g., in a continuous auction market, oralso operate as an order accumulation buffer for a batch auction market.

A market data module 112 may be included to collect market data andprepare the data for transmission to users. A risk management module 114may be included to compute and determine a user's risk utilization inrelation to the user's defined risk thresholds. The risk managementmodule 114 may also be configured to determine risk assessments orexposure levels in connection with positions held by a marketparticipant. The risk management module 114 may be configured toadminister, manage or maintain one or more margining mechanismsimplemented by the Exchange Computer System 100. Such administration,management or maintenance may include managing a number of databaserecords reflective of margin accounts of the market participants. Insome embodiments, the risk management module 114 implements one or moreaspects of the disclosed embodiments, including, for instance, principalcomponent analysis (PCA) based margining, in connection with interestrate swap (IRS) portfolios, as described herein.

A message management module 116 may be included to, among other things,receive, and extract orders from, electronic data transaction requestmessages. The message management module 116 may define a point ofingress into the Exchange Computer System 100 where messages are orderedand considered to be received by the system. This may be considered apoint of determinism in the Exchange Computer System 100 that definesthe earliest point where the system can ascribe an order of receipt toarriving messages. The point of determinism may or may not be at or nearthe demarcation point between the Exchange Computer System 100 and apublic/internet network infrastructure. The message management module116 processes messages by interpreting the contents of a message basedon the message transmit protocol, such as the transmission controlprotocol (“TCP”), to provide the content of the message for furtherprocessing by the Exchange Computer System.

The message management module 116 may also be configured to detectcharacteristics of an order for a transaction to be undertaken in anelectronic marketplace. For example, the message management module 116may identify and extract order content such as a price, product, volume,and associated market participant for an order. The message managementmodule 116 may also identify and extract data indicating an action to beexecuted by the Exchange Computer System 100 with respect to theextracted order. For example, the message management module 116 maydetermine the transaction type of the transaction requested in a givenmessage. A message may include an instruction to perform a type oftransaction. The transaction type may be, in one embodiment, arequest/offer/order to either buy or sell a specified quantity or unitsof a financial instrument at a specified price or value. The messagemanagement module 116 may also identify and extract other orderinformation and other actions associated with the extracted order. Allextracted order characteristics, other information, and associatedactions extracted from a message for an order may be collectivelyconsidered an order as described and referenced herein.

Order or message characteristics may include, for example, the state ofthe system after a message is received, arrival time (e.g., the time amessage arrives at the MSG or Market Segment Gateway), message type(e.g., new, modify, cancel), and the number of matches generated by amessage. Order or message characteristics may also include marketparticipant side (e.g., buyer or seller) or time in force (e.g., a gooduntil end of day order that is good for the full trading day, a gooduntil canceled order that rests on the order book until matched, or afill or kill order that is canceled if not filled immediately, or a filland kill order (FOK) that is filled to the maximum amount possible, andany remaining or unfilled/unsatisfied quantity is not stored on thebooks or allowed to rest).

An order processing module 118 may be included to decompose delta-based,spread instrument, bulk and other types of composite orders forprocessing by the order book module 110 and/or the match engine module106. The order processing module 118 may also be used to implement oneor more procedures related to clearing an order. The order may becommunicated from the message management module 118 to the orderprocessing module 118. The order processing module 118 may be configuredto interpret the communicated order, and manage the ordercharacteristics, other information, and associated actions as they areprocessed through an order book module 110 and eventually transacted onan electronic market. For example, the order processing module 118 maystore the order characteristics and other content and execute theassociated actions. In an embodiment, the order processing module mayexecute an associated action of placing the order into an order book foran electronic trading system managed by the order book module 110. In anembodiment, placing an order into an order book and/or into anelectronic trading system may be considered a primary action for anorder. The order processing module 118 may be configured in variousarrangements, and may be configured as part of the order book module110, part of the message management module 118, or as an independentfunctioning module.

As an intermediary to electronic trading transactions, the exchangebears a certain amount of risk in each transaction that takes place. Tothat end, the clearing house implements risk management mechanisms toprotect the exchange. One or more of the modules of the ExchangeComputer System 100 may be configured to determine settlement prices forconstituent contracts, such as deferred month contracts, of spreadinstruments, such as for example, settlement module. A settlement module(or settlement processor or other payment processor) may be included toprovide one or more functions related to settling or otherwiseadministering transactions cleared by the exchange. Settlement module ofthe Exchange Computer System 100 may implement one or more settlementprice determination techniques. Settlement-related functions need not belimited to actions or events occurring at the end of a contract term.For instance, in some embodiments, settlement-related functions mayinclude or involve daily or other mark to market settlements formargining purposes. In some cases, the settlement module may beconfigured to communicate with the trade database 108 (or thememory(ies) on which the trade database 108 is stored) and/or todetermine a payment amount based on a spot price, the price of thefutures contract or other financial instrument, or other price data, atvarious times. The determination may be made at one or more points intime during the term of the financial instrument in connection with amargining mechanism. For example, the settlement module may be used todetermine a mark to market amount on a daily basis during the term ofthe financial instrument. Such determinations may also be made on asettlement date for the financial instrument for the purposes of finalsettlement.

In some embodiments, the settlement module may be integrated to anydesired extent with one or more of the other modules or processors ofthe Exchange Computer System 100. For example, the settlement module andthe risk management module 114 may be integrated to any desired extent.In some cases, one or more margining procedures or other aspects of themargining mechanism(s) may be implemented by the settlement module.

One or more of the above-described modules of the Exchange ComputerSystem 100 may be used to gather or obtain data to support thesettlement price determination, as well as a subsequent marginrequirement determination. For example, the order book module 110 and/orthe market data module 112 may be used to receive, access, or otherwiseobtain market data, such as bid-offer values of orders currently on theorder books. The trade database 108 may be used to receive, access, orotherwise obtain trade data indicative of the prices and volumes oftrades that were recently executed in a number of markets. In somecases, transaction data (and/or bid/ask data) may be gathered orobtained from open outcry pits and/or other sources and incorporatedinto the trade and market data from the electronic trading system(s).

The historical volatility module 142 is configured to calculate historicvolatility values based on prices, for example, prices previouslydetermined by the settlement module or prices stored in the order bookmodule 110 or distributed by the market data module 112. The historicalvolatility module 142 may calculate volatility from a series of pricesover a time period. The historical volatility module 142 may requestprice information for a particular asset from the order book module 110and/or the market data module 112. The historical volatility module 142may calculate historical volatility values based on the variance of theprice information, for example, using equation 1 or 2.

The implied volatility module 143 is configured to calculate future orimplied volatility values based on prices, for example, option prices.The implied volatility module 143 may request price information foroptions on the particular asset across a series of expiration dates fromthe order book module 110 and/or the market data module 112. The impliedvolatility module 143 may calculate implied volatility values from theprice information across expiration date using a predetermined model, asdescribed by Equation 3.

The volatility synthesis module 144 receives data from the historicalvolatility module 142 and the implied volatility module 143 to synthesisan index combined the historical volatility data and the impliedvolatility data. The volatility synthesis module 144 may generate amatrix indexed by an anchor data The anchor data is the current date orpivot date dividing the historical volatility data from the impliedvolatility data.

It should be appreciated that concurrent processing limits may bedefined by or imposed separately or in combination on one or more of thetrading system components, including the user database 102, the accountdata module 104, the match engine module 106, the trade database 108,the order book module 110, the market data module 112, the riskmanagement module 114, the message management module 116, the orderprocessing module 118, the settlement module 120, or other component ofthe Exchange Computer System 100.

The disclosed mechanisms may be implemented at any logical and/orphysical point(s), or combinations thereof, at which the relevantinformation/data (e.g., message traffic and responses thereto) may bemonitored or flows or is otherwise accessible or measurable, includingone or more gateway devices, modems, the computers or terminals of oneor more market participants, e.g., client computers, etc.

One skilled in the art will appreciate that one or more modulesdescribed herein may be implemented using, among other things, atangible computer-readable medium comprising computer-executableinstructions (e.g., executable software code). Alternatively, modulesmay be implemented as software code, firmware code, specificallyconfigured hardware or processors, and/or a combination of theaforementioned. For example, the modules may be embodied as part of anexchange 100 for financial instruments. It should be appreciated thedisclosed embodiments may be implemented as a different or separatemodule of the Exchange Computer System 100, or a separate computersystem coupled with the Exchange Computer System 100 so as to haveaccess to margin account record, pricing, and/or other data. Asdescribed herein, the disclosed embodiments may be implemented as acentrally accessible system or as a distributed system, e.g., where someof the disclosed functions are performed by the computer systems of themarket participants.

The trading network environment shown in FIG. 1 includes exemplarycomputer devices 114, 116, 118, 120 and 122 which depict differentexemplary methods or media by which a computer device may be coupledwith the Exchange Computer System 100 or by which a user maycommunicate, e.g., send and receive, trade or other informationtherewith. It should be appreciated that the types of computer devicesdeployed by traders and the methods and media by which they communicatewith the Exchange Computer System 100 is implementation dependent andmay vary and that not all of the depicted computer devices and/ormeans/media of communication may be used and that other computer devicesand/or means/media of communications, now available or later developedmay be used. Each computer device, which may comprise a computer 200described in more detail with respect to FIG. 2, may include a centralprocessor, specifically configured or otherwise, that controls theoverall operation of the computer and a system bus that connects thecentral processor to one or more conventional components, such as anetwork card or modem. Each computer device may also include a varietyof interface units and drives for reading and writing data or files andcommunicating with other computer devices and with the Exchange ComputerSystem 100. Depending on the type of computer device, a user caninteract with the computer with a keyboard, pointing device, microphone,pen device or other input device now available or later developed.

An exemplary computer device 114 is shown directly connected to ExchangeComputer System 100, such as via a T1 line, a common local area network(LAN) or other wired and/or wireless medium for connecting computerdevices, such as the network 220 shown in FIG. 11 and described belowwith respect thereto. The exemplary computer device 114 is further shownconnected to a radio 132. The user of radio 132, which may include acellular telephone, smart phone, or other wireless proprietary and/ornon-proprietary device, may be a trader or exchange employee. The radiouser may transmit orders or other information to the exemplary computerdevice 114 or a user thereof. The user of the exemplary computer device114, or the exemplary computer device 114 alone and/or autonomously, maythen transmit the trade or other information to the Exchange ComputerSystem 100.

Exemplary computer devices 116 and 118 are coupled with a local areanetwork (“LAN”) 124 which may be configured in one or more of thewell-known LAN topologies, e.g., star, daisy chain, etc., and may use avariety of different protocols, such as Ethernet, TCP/IP, etc. Theexemplary computer devices 116 and 118 may communicate with each otherand with other computer and other devices which are coupled with the LAN124. Computer and other devices may be coupled with the LAN 124 viatwisted pair wires, coaxial cable, fiber optics or other wired orwireless media. As shown in FIG. 4, an exemplary wireless personaldigital assistant device (“PDA”) 122, such as a mobile telephone, tabletbased compute device, or other wireless device, may communicate with theLAN 124 and/or the Internet 126 via radio waves, such as via Wi-Fi,Bluetooth and/or a cellular telephone based data communicationsprotocol. PDA 122 may also communicate with Exchange Computer System 100via a conventional wireless hub 128.

FIG. 1 also shows the LAN 124 coupled with a wide area network (“WAN”)126 which may be comprised of one or more public or private wired orwireless networks. In one embodiment, the WAN 126 includes the Internet126. The LAN 124 may include a router to connect LAN 124 to the Internet126. Exemplary computer device 120 is shown coupled directly to theInternet 126, such as via a modem, DSL line, satellite dish or any otherdevice for connecting a computer device to the Internet 126 via aservice provider therefore as is known. LAN 124 and/or WAN 126 may bethe same as the network 220 shown in FIG. 5 and described below withrespect thereto.

As was described above, the users of the Exchange Computer System 100may include one or more market makers 130 which may maintain a market byproviding constant bid and offer prices for a derivative or security tothe Exchange Computer System 100, such as via one of the exemplarycomputer devices depicted. The Exchange Computer System 100 may alsoexchange information with other match or trade engines, such as tradeengine 138. One skilled in the art will appreciate that numerousadditional computers and systems may be coupled to Exchange ComputerSystem 100. Such computers and systems may include clearing, regulatoryand fee systems.

The operations of computer devices and systems shown in FIG. 10 may becontrolled by computer-executable instructions stored on anon-transitory computer-readable medium. For example, the exemplarycomputer device 116 may store computer-executable instructions forreceiving order information from a user, transmitting that orderinformation to Exchange Computer System 100 in electronic messages,extracting the order information from the electronic messages, executingactions relating to the messages, and/or calculating values fromcharacteristics of the extracted order to facilitate matching orders andexecuting trades. In another example, the exemplary computer device 118may include computer-executable instructions for receiving market datafrom Exchange Computer System 100 and displaying that information to auser. In another example, the exemplary computer device 118 may includea non-transitory computer-readable medium that stores instructions forpredicting and/or publishing a current response time or current matchengine latency as described herein.

Numerous additional servers, computers, handheld devices, personaldigital assistants, telephones and other devices may also be connectedto Exchange Computer System 100. Moreover, one skilled in the art willappreciate that the topology shown in FIG. 1 is merely an example andthat the components shown in FIG. 1 may include other components notshown and be connected by numerous alternative topologies.

Referring now to FIG. 2, an illustrative embodiment of a generalcomputer system 200 is shown. The computer system 200 can include a setof instructions that can be executed to cause the computer system 200 toperform any one or more of the methods or computer-based functionsdisclosed herein. The computer system 200 may operate as a standalonedevice or may be connected, e.g., using a network, to other computersystems or peripheral devices. Any of the components discussed herein,such as processor 202, may be a computer system 200 or a component inthe computer system 200. The computer system 200 may be specificallyconfigured to implement a match engine, margin processing, payment, orclearing function on behalf of an exchange, such as the ChicagoMercantile Exchange Inc., of which the disclosed embodiments are acomponent thereof.

In a networked deployment, the computer system 200 may operate in thecapacity of a server or as a client user computer in a client-serveruser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 200 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a palmtop computer, a laptopcomputer, a desktop computer, a communications device, a wirelesstelephone, a land-line telephone, a control system, a camera, a scanner,a facsimile machine, a printer, a pager, a personal trusted device, aweb appliance, a network router, switch or bridge, or any other machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. In a particularembodiment, the computer system 200 can be implemented using electronicdevices that provide voice, video, or data communication. Further, whilea single computer system 200 is illustrated, the term “system” shallalso be taken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

As illustrated in FIG. 2, the computer system 200 may include aprocessor 202, e.g., a volatility processor implemented by a centralprocessing unit (CPU), a graphics processing unit (GPU), or both. Theprocessor 202 may be a component in a variety of systems. For example,the processor 202 may be part of a standard personal computer or aworkstation. The processor 202 may be one or more general processors,digital signal processors, specifically configured processors,application specific integrated circuits, field programmable gatearrays, servers, networks, digital circuits, analog circuits,combinations thereof, or other now known or later developed devices foranalyzing and processing data. The processor 202 may implement asoftware program, such as code generated manually (i.e., programmed).

The computer system 200 may include a memory 204 that can communicatevia a bus 208. The memory 204 may be a main memory, a static memory, ora dynamic memory. The memory 204 may include, but is not limited to,computer-readable storage media such as various types of volatile andnon-volatile storage media, including but not limited to random-accessmemory, read-only memory, programmable read-only memory, electricallyprogrammable read-only memory, electrically erasable read-only memory,flash memory, magnetic tape or disk, optical media and the like. In oneembodiment, the memory 204 includes a cache or random-access memory forthe processor 202. In alternative embodiments, the memory 204 isseparate from the processor 202, such as a cache memory of a processor,the system memory, or other memory. The memory 204 may be an externalstorage device or database for storing data. Examples include a harddrive, compact disk (“CD”), digital video disc (“DVD”), memory card,memory stick, floppy disk, universal serial bus (“USB”) memory device,or any other device operative to store data. The memory 204 is operableto store instructions executable by the processor 202. The functions,acts or tasks illustrated in the figures or described herein may beperformed by the programmed processor 202 executing the instructions 212stored in the memory 204. The functions, acts or tasks are independentof the particular type of instructions set, storage media, processor orprocessing strategy and may be performed by software, hardware,integrated circuits, firmware, micro-code and the like, operating aloneor in combination. Likewise, processing strategies may includemultiprocessing, multitasking, parallel processing and the like.

As shown, the computer system 200 may further include a display unit214, such as a liquid crystal display (LCD), an organic light emittingdiode (OLED), a flat panel display, a solid-state display, a cathode raytube (CRT), a projector, a printer or other now known or later developeddisplay device for outputting determined information. The display 214may act as an interface for the user to see the functioning of theprocessor 202, or specifically as an interface with the software storedin the memory 204 or in the drive unit 206.

Additionally, the computer system 200 may include an input device 216configured to allow a user to interact with any of the components ofsystem 200. The input device 216 may be a number pad, a keyboard, or acursor control device, such as a mouse, or a joystick, touch screendisplay, remote control or any other device operative to interact withthe system 200.

In a particular embodiment, as depicted in FIG. 2, the computer system200 may also include a disk or optical drive unit 206. The disk driveunit 206 may include a computer-readable medium 210 in which one or moresets of instructions 212, e.g., software, can be embedded. Further, theinstructions 212 may embody one or more of the methods or logic asdescribed herein. In a particular embodiment, the instructions 212 mayreside completely, or at least partially, within the memory 204 and/orwithin the processor 202 during execution by the computer system 200.The memory 204 and the processor 202 also may include computer-readablemedia as discussed herein.

The present disclosure contemplates a computer-readable medium thatincludes instructions 212 or receives and executes instructions 212responsive to a propagated signal, so that a device connected to anetwork 220 can communicate voice, video, audio, images or any otherdata over the network 220. Further, the instructions 212 may betransmitted or received over the network 220 via a communicationinterface 218. The communication interface 218 may be a part of theprocessor 202 or may be a separate component. The communicationinterface 218 may be created in software or may be a physical connectionin hardware. The communication interface 218 is configured to connectwith a network 220, external media, the display 214, or any othercomponents in system 200, or combinations thereof. The connection withthe network 220 may be a physical connection, such as a wired Ethernetconnection or may be established wirelessly. Likewise, the additionalconnections with other components of the system 200 may be physicalconnections or may be established wirelessly.

The network 220 may include wired networks, wireless networks, orcombinations thereof. The wireless network may be a cellular telephonenetwork, an 802.11, 802.16, 802.20, or WiMax network. Further, thenetwork 220 may be a public network, such as the Internet, a privatenetwork, such as an intranet, or combinations thereof, and may utilize avariety of networking protocols now available or later developedincluding, but not limited to, TCP/IP based networking protocols.

Embodiments of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Embodiments ofthe subject matter described in this specification can be implemented asone or more computer program products, i.e., one or more modules ofcomputer program instructions encoded on a computer-readable medium forexecution by, or to control the operation of, data processing apparatus.While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single-medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein. The computer-readablemedium can be a machine-readable storage device, a machine-readablestorage substrate, a memory device, or a combination of one or more ofthem. The term “data processing apparatus” encompasses all apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, or multiple processors or computers.The apparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom-access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disc or tapes or other storage device to capturecarrier wave signals such as a signal communicated over a transmissionmedium. A digital file attachment to an e-mail or other self-containedinformation archive or set of archives may be considered a distributionmedium that is a tangible storage medium. Accordingly, the disclosure isconsidered to include any one or more of a computer-readable medium or adistribution medium and other equivalents and successor media, in whichdata or instructions may be stored.

In an alternative embodiment, dedicated or otherwise specificallyconfigured hardware implementations, such as application specificintegrated circuits, programmable logic arrays and other hardwaredevices, can be constructed to implement one or more of the methodsdescribed herein. Applications that may include the apparatus andsystems of various embodiments can broadly include a variety ofelectronic and computer systems. One or more embodiments describedherein may implement functions using two or more specific interconnectedhardware modules or devices with related control and data signals thatcan be communicated between and through the modules, or as portions ofan application-specific integrated circuit. Accordingly, the presentsystem encompasses software, firmware, and hardware implementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the invention is not limited to suchstandards and protocols. For example, standards for Internet and otherpacket switched network transmission (e.g., TCP/IP, UDP/IP, HTML, HTTP,HTTPS) represent examples of the state of the art. Such standards areperiodically superseded by faster or more efficient equivalents havingessentially the same functions. Accordingly, replacement standards andprotocols having the same or similar functions as those disclosed hereinare considered equivalents thereof.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a standalone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andanyone or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random-access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, e.g., a mobile telephone, a personal digital assistant(PDA), a mobile audio player, a Global Positioning System (GPS)receiver, to name just a few. Computer-readable media suitable forstoring computer program instructions and data include all forms ofnon-volatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto optical discs; and CD ROM and DVD-ROM discs. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

As used herein, the terms “microprocessor” or “general-purposeprocessor” (“GPP”) may refer to a hardware device that fetchesinstructions and data from a memory or storage device and executes thoseinstructions (for example, an Intel Xeon processor or an AMD Opteronprocessor) to then, for example, process the data in accordancetherewith. The term “reconfigurable logic” may refer to any logictechnology whose form and function can be significantly altered (i.e.,reconfigured) in the field post-manufacture as opposed to amicroprocessor, whose function can change post-manufacture, e.g. viacomputer executable software code, but whose form, e.g. thearrangement/layout and interconnection of logical structures, is fixedat manufacture. The term “software” may refer to data processingfunctionality that is deployed on a GPP. The term “firmware” may referto data processing functionality that is deployed on reconfigurablelogic. One example of a reconfigurable logic is a field programmablegate array (“FPGA”) which is a reconfigurable integrated circuit. AnFPGA may contain programmable logic components called “logic blocks”,and a hierarchy of reconfigurable interconnects that allow the blocks tobe “wired together”, somewhat like many (changeable) logic gates thatcan be inter-wired in (many) different configurations. Logic blocks maybe configured to perform complex combinatorial functions, or merelysimple logic gates like AND, OR, NOT and XOR. An FPGA may furtherinclude memory elements, which may be simple flip-flops or more completeblocks of memory.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a devicehaving a display, e.g., a CRT (cathode ray tube) or LCD (liquid crystaldisplay) monitor, for displaying information to the user and a keyboardand a pointing device, e.g., a mouse or a trackball, by which the usercan provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. Feedback provided to theuser can be any form of sensory feedback, e.g., visual feedback,auditory feedback, or tactile feedback. Input from the user can bereceived in any form, including acoustic, speech, or tactile input.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back end component,e.g., a data server, or that includes a middleware component, e.g., anapplication server, or that includes a front end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), e.g., the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

It should be appreciated that the disclosed embodiments may beapplicable to other types of messages depending upon the implementation.Further, the messages may comprise one or more data packets, datagramsor other collection of data formatted, arranged configured and/orpackaged in a particular one or more protocols, e.g., the FIX protocol,TCP/IP, Ethernet, etc., suitable for transmission via a network as wasdescribed, such as the message format and/or protocols described in U.S.Pat. No. 7,831,491 and U.S. Patent Publication No. 2005/0096999 A1, bothof which are incorporated by reference herein in their entireties andrelied upon. Further, the disclosed message management system may beimplemented using an open message standard implementation, such as FIX,FIX Binary, FIX/FAST, or by an exchange-provided API.

The embodiments described herein utilize trade related electronicmessages such as mass quote messages, individual order messages,modification messages, cancellation messages, etc., so as to enacttrading activity in an electronic market. The trading entity and/ormarket participant may have one or multiple trading terminals associatedwith the session. Furthermore, the financial instruments may befinancial derivative products. Derivative products may include futurescontracts, options on futures contracts, futures contracts that arefunctions of or related to other futures contracts, swaps, swaptions, orother financial instruments that have their price related to or derivedfrom an underlying product, security, commodity, equity, index, orinterest rate product. In one embodiment, the orders are for optionscontracts that belong to a common option class. Orders may also be forbaskets, quadrants, other combinations of financial instruments, etc.The option contracts may have a plurality of strike prices and/orcomprise put and call contracts. A mass quote message may be received atan exchange. As used herein, an Exchange Computing System 100 includes aplace or system that receives and/or executes orders.

In an embodiment, a plurality of electronic messages is received fromthe network. The plurality of electronic messages may be received at anetwork interface for the electronic trading system. The plurality ofelectronic messages may be sent from market participants. The pluralityof messages may include order characteristics and be associated withactions to be executed with respect to an order that may be extractedfrom the order characteristics. The action may involve any action asassociated with transacting the order in an electronic trading system.The actions may involve placing the orders within a particular marketand/or order book of a market in the electronic trading system.

In an embodiment, an incoming transaction may be received. The incomingtransaction may be from, and therefore associated with, a marketparticipant of an electronic market managed by an electronic tradingsystem. The transaction may involve an order as extracted from areceived message, and may have an associated action. The actions mayinvolve placing an order to buy or sell a financial product in theelectronic market, or modifying or deleting such an order. In anembodiment, the financial product may be based on an associatedfinancial instrument which the electronic market is established totrade.

In an embodiment, the action associated with the transaction isdetermined. For example, it may be determined whether the incomingtransaction comprises an order to buy or sell a quantity of theassociated financial instrument or an order to modify or cancel anexisting order in the electronic market. Orders to buy or sell andorders to modify or cancel may be acted upon differently by theelectronic market. For example, data indicative of differentcharacteristics of the types of orders may be stored.

In an embodiment, data relating to the received transaction is stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer-readable medium 210, may be used to store data, as is describedwith respect to FIG. 2 in further detail herein. Data may be storedrelating received transactions for a period of time, indefinitely, orfor a rolling most recent time period such that the stored data isindicative of the market participant's recent activity in the electronicmarket.

If and/or when a transaction is determined to be an order to modify orcancel a previously placed, or existing, order, data indicative of theseactions may be stored. For example, data indicative of a running countof a number or frequency of the receipt of modify or cancel orders fromthe market participant may be stored. A number may be a total number ofmodify or cancel orders received from the market participant, or anumber of modify or cancel orders received from the market participantover a specified time. A frequency may be a time-based frequency, as ina number of cancel or modify orders per unit of time, or a number ofcancel or modify orders received from the market participant as apercentage of total transactions received from the participant, whichmay or may not be limited by a specified length of time.

If and/or when a transaction is determined to be an order to buy or sella financial product, or financial instrument, other indicative data maybe stored. For example, data indicative of quantity and associated priceof the order to buy or sell may be stored.

Data indicative of attempts to match incoming orders may also be stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer-readable medium 210, may be used to store data, as is describedwith respect to FIG. 2. The acts of the process as described herein mayalso be repeated. As such, data for multiple received transactions formultiple market participants may be stored and used as describe herein.

The order processing module 118 may also store data indicative ofcharacteristics of the extracted orders. For example, the orderprocessing module may store data indicative of orders having anassociated modify or cancel action, such as by recording a count of thenumber of such orders associated with particular market participants.The order processing module may also store data indicative of quantitiesand associated prices of orders to buy or sell a product placed in themarket order book 110, as associated with particular marketparticipants.

Also, the order processing module 118 may be configured to calculate andassociate with particular orders a value indicative of an associatedmarket participant's market activity quality, which is a valueindicative of whether the market participant's market activity increasesor tends to increase liquidity of a market. This value may be determinedbased on the price of the particular order, previously stored quantitiesof orders from the associated market participant, the previously storeddata indicative of previously received orders to modify or cancel asassociated with the market participant, and previously stored dataindicative of a result of the attempt to match previously receivedorders stored in association with the market participant. The orderprocessing module 118 may determine or otherwise calculate scoresindicative of the quality value based on these stored extracted ordercharacteristics, such as an MQI as described herein.

Further, electronic trading systems may perform actions on orders placedfrom received messages based on various characteristics of the messagesand/or market participants associated with the messages. These actionsmay include matching the orders either during a continuous auctionprocess, or at the conclusion of a collection period during a batchauction process. The matching of orders may be by any technique.

The matching of orders may occur based on a priority indicated by thecharacteristics of orders and market participants associated with theorders. Orders having a higher priority may be matched before orders ofa lower priority. Such priority may be determined using varioustechniques. For example, orders that were indicated by messages receivedearlier may receive a higher priority to match than orders that wereindicated by messages received later. Also, scoring or grading of thecharacteristics may provide for priority determination. Data indicativeof order matches may be stored by a match engine and/or an orderprocessing module 118, and used for determining MQI scores of marketparticipants.

Example Users

Generally, a market may involve market makers, such as marketparticipants who consistently provide bids and/or offers at specificprices in a manner typically conducive to balancing risk, and markettakers who may be willing to execute transactions at prevailing bids oroffers may be characterized by more aggressive actions so as to maintainrisk and/or exposure as a speculative investment strategy. From analternate perspective, a market maker may be considered a marketparticipant who places an order to sell at a price at which there is nota previously or concurrently provided counter order. Similarly, a markettaker may be considered a market participant who places an order to buyat a price at which there is a previously or concurrently providedcounter order. A balanced and efficient market may involve both marketmakers and market takers, coexisting in a mutually beneficial basis. Themutual existence, when functioning properly, may facilitate liquidity inthe market such that a market may exist with “tight” bid-ask spreads(e.g., small difference between bid and ask prices) and a “deep” volumefrom many currently provided orders such that large quantity orders maybe executed without driving prices significantly higher or lower.

As such, both market participant types are useful in generatingliquidity in a market, but specific characteristics of market activitytaken by market participants may provide an indication of a particularmarket participant's effect on market liquidity. For example, a MarketQuality Index (“MQI”) of an order may be determined using thecharacteristics. An MQI may be considered a value indicating alikelihood that a particular order will improve or facilitate liquidityin a market. That is, the value may indicate a likelihood that the orderwill increase a probability that subsequent requests and transactionfrom other market participants will be satisfied. As such, an MQI may bedetermined based on a proximity of the entered price of an order to amidpoint of a current bid-ask price spread, a size of the entered order,a volume or quantity of previously filled orders of the marketparticipant associated with the order, and/or a frequency ofmodifications to previous orders of the market participant associatedwith the order. In this way, an electronic trading system may functionto assess and/or assign an MQI to received electronic messages toestablish messages that have a higher value to the system, and thus thesystem may use computing resources more efficiently by expendingresources to match orders of the higher value messages prior toexpending resources of lower value messages.

While an MQI may be applied to any or all market participants, such anindex may also be applied only to a subset thereof, such as large marketparticipants, or market participants whose market activity as measuredin terms of average daily message traffic over a limited historical timeperiod exceeds a specified number. For example, a market participantgenerating more than 500, 1,000, or even 10,000 market messages per daymay be considered a large market participant.

An exchange provides one or more markets for the purchase and sale ofvarious types of products including financial instruments such asstocks, bonds, futures contracts, options, currency, cash, and othersimilar instruments. Agricultural products and commodities are alsoexamples of products traded on such exchanges. A futures contract is aproduct that is a contract for the future delivery of another financialinstrument such as a quantity of grains, metals, oils, bonds, currency,or cash. Generally, each exchange establishes a specification for eachmarket provided thereby that defines at least the product traded in themarket, minimum quantities that must be traded, and minimum changes inprice (e.g., tick size). For some types of products (e.g., futures oroptions), the specification further defines a quantity of the underlyingproduct represented by one unit (or lot) of the product, and deliveryand expiration dates. As will be described, the exchange may furtherdefine the matching algorithm, or rules, by which incoming orders willbe matched/allocated to resting orders.

Matching and Transaction Processing

Market participants, e.g., traders, use software to send orders ormessages to the trading platform. The order identifies the product, thequantity of the product the trader wishes to trade, a price at which thetrader wishes to trade the product, and a direction of the order (i.e.,whether the order is a bid, i.e., an offer to buy, or an ask, i.e., anoffer to sell). It will be appreciated that there may be other ordertypes or messages that traders can send including requests to modify orcancel a previously submitted order.

The Exchange Computer System monitors incoming orders received therebyand attempts to identify, i.e., match or allocate, as described herein,one or more previously received, but not yet matched, orders, i.e.,limit orders to buy or sell a given quantity at a given price, referredto as “resting” orders, stored in an order book database, wherein eachidentified order is contra to the incoming order and has a favorableprice relative to the incoming order. An incoming order may be an“aggressor” order, i.e., a market order to sell a given quantity atwhatever may be the current resting bid order price(s) or a market orderto buy a given quantity at whatever may be the current resting ask orderprice(s). An incoming order may be a “market making” order, i.e., amarket order to buy or sell at a price for which there are currently noresting orders. In particular, if the incoming order is a bid, i.e., anoffer to buy, then the identified order(s) will be an ask, i.e., anoffer to sell, at a price that is identical to or higher than the bidprice. Similarly, if the incoming order is an ask, i.e., an offer tosell, the identified order(s) will be a bid, i.e., an offer to buy, at aprice that is identical to or lower than the offer price.

An exchange computing system may receive conditional orders or messagesfor a data object, where the order may include two prices or values: areference value and a stop value. A conditional order may be configuredso that when a product represented by the data object trades at thereference price, the stop order is activated at the stop value. Forexample, if the exchange computing system's order management moduleincludes a stop order with a stop price of 5 and a limit price of 1 fora product, and a trade at 5 (i.e., the stop price of the stop order)occurs, then the exchange computing system attempts to trade at 1 (i.e.,the limit price of the stop order). In other words, a stop order is aconditional order to trade (or execute) at the limit price that istriggered (or elected) when a trade at the stop price occurs.

Stop orders also rest on, or are maintained in, an order book to monitorfor a trade at the stop price, which triggers an attempted trade at thelimit price. In some embodiments, a triggered limit price for a stoporder may be treated as an incoming order.

Upon identification (matching) of a contra order(s), a minimum of thequantities associated with the identified order and the incoming orderis matched and that quantity of each of the identified and incomingorders become two halves of a matched trade that is sent to a clearinghouse. The Exchange Computer System considers each identified order inthis manner until either all of the identified orders have beenconsidered or all of the quantity associated with the incoming order hasbeen matched, i.e., the order has been filled. If any quantity of theincoming order remains, an entry may be created in the order bookdatabase and information regarding the incoming order is recordedtherein, i.e., a resting order is placed on the order book for theremaining quantity to await a subsequent incoming order counter thereto.

It should be appreciated that in electronic trading systems implementedvia an exchange computing system, a trade price (or match value) maydiffer from (i.e., be better for the submitter, e.g., lower than asubmitted buy price or higher than a submitted sell price) the limitprice that is submitted, e.g., a price included in an incoming message,or a triggered limit price from a stop order.

As used herein, “better” than a reference value means lower than thereference value if the transaction is a purchase (or acquire)transaction, and higher than the reference value if the transaction is asell transaction. Said another way, for purchase (or acquire)transactions, lower values are better, and for relinquish or selltransactions, higher values are better.

Traders access the markets on a trading platform using trading softwarethat receives and displays at least a portion of the order book for amarket, i.e., at least a portion of the currently resting orders,enables a trader to provide parameters for an order for the producttraded in the market, and transmits the order to the Exchange ComputerSystem. The trading software typically includes a graphical userinterface to display at least a price and quantity of some of theentries in the order book associated with the market. The number ofentries of the order book displayed is generally preconfigured by thetrading software, limited by the Exchange Computer System, or customizedby the user. Some graphical user interfaces display order books ofmultiple markets of one or more trading platforms. The trader may be anindividual who trades on his/her behalf, a broker trading on behalf ofanother person or entity, a group, or an entity. Furthermore, the tradermay be a system that automatically generates and submits orders.

If the Exchange Computer System identifies that an incoming market ordermay be filled by a combination of multiple resting orders, e.g., theresting order at the best price only partially fills the incoming order,the Exchange Computer System may allocate the remaining quantity of theincoming order, i.e., that which was not filled by the resting order atthe best price, among such identified orders in accordance withprioritization and allocation rules/algorithms, referred to as“allocation algorithms” or “matching algorithms,” as, for example, maybe defined in the specification of the particular financial product ordefined by the exchange for multiple financial products. Similarly, ifthe Exchange Computer System identifies multiple orders contra to theincoming limit order and that have an identical price which is favorableto the price of the incoming order, i.e., the price is equal to orbetter, e.g., lower if the incoming order is a buy (or instruction topurchase, or instruction to acquire) or higher if the incoming order isa sell (or instruction to relinquish), than the price of the incomingorder, the Exchange Computer System may allocate the quantity of theincoming order among such identified orders in accordance with thematching algorithms as, for example, may be defined in the specificationof the particular financial product or defined by the exchange formultiple financial products.

An exchange responds to inputs, such as trader orders, cancellation,etc., in a manner as expected by the market participants, such as basedon market data, e.g., prices, available counter-orders, etc., to providean expected level of certainty that transactions will occur in aconsistent and predictable manner and without unknown or unascertainablerisks. Accordingly, the method by which incoming orders are matched withresting orders must be defined so that market participants have anexpectation of what the result will be when they place an order or haveresting orders and an incoming order is received, even if the expectedresult is, in fact, at least partially unpredictable due to somecomponent of the process being random or arbitrary or due to marketparticipants having imperfect or less than all information, e.g.,unknown position of an order in an order book. Typically, the exchangedefines the matching/allocation algorithm that will be used for aparticular financial product, with or without input from the marketparticipants. Once defined for a particular product, thematching/allocation algorithm is typically not altered, except inlimited circumstance, such as to correct errors or improve operation, soas not to disrupt trader expectations. It will be appreciated thatdifferent products offered by a particular exchange may use differentmatching algorithms.

For example, a first-in/first-out (FIFO) matching algorithm, alsoreferred to as a “Price Time” algorithm, considers each identified ordersequentially in accordance with when the identified order was received.The quantity of the incoming order is matched to the quantity of theidentified order at the best price received earliest, then quantities ofthe next earliest best price orders, and so on until the quantity of theincoming order is exhausted. Some product specifications define the useof a pro-rata matching algorithm, wherein a quantity of an incomingorder is allocated to each of plurality of identified ordersproportionally. Some Exchange Computer Systems provide a priority tocertain standing orders in particular markets. An example of such anorder is the first order that improves a price (i.e., improves themarket) for the product during a trading session. To be given priority,the trading platform may require that the quantity associated with theorder is at least a minimum quantity. Further, some Exchange ComputerSystems cap the quantity of an incoming order that is allocated to astanding order on the basis of a priority for certain markets. Inaddition, some Exchange Computer Systems may give a preference to orderssubmitted by a trader who is designated as a market maker for theproduct. Other Exchange Computer Systems may use other criteria todetermine whether orders submitted by a particular trader are given apreference. Typically, when the Exchange Computer System allocates aquantity of an incoming order to a plurality of identified orders at thesame price, the trading host allocates a quantity of the incoming orderto any orders that have been given priority. The Exchange ComputerSystem thereafter allocates any remaining quantity of the incoming orderto orders submitted by traders designated to have a preference, and thenallocates any still remaining quantity of the incoming order using theFIFO or pro-rata algorithms. Pro-rata algorithms used in some marketsmay require that an allocation provided to a particular order inaccordance with the pro-rata algorithm must meet at least a minimumallocation quantity. Any orders that do not meet or exceed the minimumallocation quantity are allocated to on a FIFO basis after the pro-rataallocation (if any quantity of the incoming order remains). Moreinformation regarding order allocation may be found in U.S. Pat. No.7,853,499, the entirety of which is incorporated by reference herein andrelied upon. Other examples of matching algorithms which may be definedfor allocation of orders of a particular financial product include:Price Explicit Time; Order Level Pro Rata; Order Level Priority ProRata; Preference Price Explicit Time; Preference Order Level Pro Rata;Preference Order Level Priority Pro Rata; Threshold Pro-Rata; PriorityThreshold Pro-Rata; Preference Threshold Pro-Rata; Priority PreferenceThreshold Pro-Rata; and Split Price-Time Pro-Rata, which are describedin U.S. patent application Ser. No. 13/534,499, filed on Jun. 27, 2012,entitled “Multiple Trade Matching Algorithms,” published as U.S. PatentApplication Publication No. 2014/0006243 A1, the entirety of which isincorporated by reference herein and relied upon.

With respect to incoming orders, some traders, such as automated and/oralgorithmic traders, attempt to respond to market events, such as tocapitalize upon a mispriced resting order or other market inefficiency,as quickly as possible. This may result in penalizing the trader whomakes an errant trade, or whose underlying trading motivations havechanged, and who cannot otherwise modify or cancel their order fasterthan other traders can submit trades there against. It may be consideredthat an electronic trading system that rewards the trader who submitstheir order first creates an incentive to either invest substantialcapital in faster trading systems, participate in the marketsubstantially to capitalize on opportunities (aggressor side/lower risktrading) as opposed to creating new opportunities (market making/higherrisk trading), modify existing systems to streamline business logic atthe cost of trade quality, or reduce one's activities and exposure inthe market. The result may be a lesser quality market and/or reducedtransaction volume, and corresponding thereto, reduced fees to theexchange.

With respect to resting orders, allocation/matching suitable restingorders to match against an incoming order can be performed, as describedherein, in many different ways. Generally, it will be appreciated thatallocation/matching algorithms are only needed when the incoming orderquantity is less than the total quantity of the suitable resting ordersas, only in this situation, is it necessary to decide which restingorder(s) will not be fully satisfied, which trader(s) will not get theirorders filled. It can be seen from the above descriptions of thematching/allocation algorithms, that they fall generally into threecategories: time priority/first-in-first-out (“FIFO”), pro rata, or ahybrid of FIFO and pro rata.

FIFO generally rewards the first trader to place an order at aparticular price and maintains this reward indefinitely. So, if a traderis the first to place an order at price X, no matter how long that orderrests and no matter how many orders may follow at the same price, assoon as a suitable incoming order is received, that first trader will bematched first. This “first mover” system may commit other traders topositions in the queue after the first move traders. Furthermore, whileit may be beneficial to give priority to a trader who is first to placean order at a given price because that trader is, in effect, taking arisk, the longer that the trader's order rests, the less beneficial itmay be. For instance, it could deter other traders from adding liquidityto the marketplace at that price because they know the first mover (andpotentially others) already occupies the front of the queue.

With a pro rata allocation, incoming orders are effectively split amongsuitable resting orders. This provides a sense of fairness in thateveryone may get some of their order filled. However, a trader who tooka risk by being first to place an order (a “market turning” order) at aprice may end up having to share an incoming order with a much latersubmitted order. Furthermore, as a pro rata allocation distributes theincoming order according to a proportion based on the resting orderquantities, traders may place orders for large quantities, which theyare willing to trade but may not necessarily want to trade, in order toincrease the proportion of an incoming order that they will receive.This results in an escalation of quantities on the order book andexposes a trader to a risk that someone may trade against one of theseorders and subject the trader to a larger trade than they intended. Inthe typical case, once an incoming order is allocated against theselarge resting orders, the traders subsequently cancel the remainingresting quantity which may frustrate other traders. Accordingly, as FIFOand pro rata both have benefits and problems, exchanges may try to usehybrid allocation/matching algorithms which attempt to balance thesebenefits and problems by combining FIFO and pro rata in some manner.However, hybrid systems define conditions or fixed rules to determinewhen FIFO should be used and when pro rata should be used. For example,a fixed percentage of an incoming order may be allocated using a FIFOmechanism with the remainder being allocated pro rata.

Spread Instruments

Traders trading on an exchange including, for example, Exchange ComputerSystem 100, often desire to trade multiple financial instruments incombination. Each component of the combination may be called a leg.Traders can submit orders for individual legs or in some cases cansubmit a single order for multiple financial instruments in anexchange-defined combination. Such orders may be called a strategyorder, a spread order, or a variety of other names.

A spread instrument may involve the simultaneous purchase of onesecurity and sale of a related security, called legs, as a unit. Thelegs of a spread instrument may be options or futures contracts, orcombinations of the two. Trades in spread instruments are executed toyield an overall net position whose value, called the spread, depends onthe difference between the prices of the legs. Spread instruments may betraded in an attempt to profit from the widening or narrowing of thespread, rather than from movement in the prices of the legs directly.Spread instruments are either “bought” or “sold” depending on whetherthe trade will profit from the widening or narrowing of the spread,respectively. An exchange often supports trading of common spreads as aunit rather than as individual legs, thus ensuring simultaneousexecution of the two legs, eliminating the execution risk of one legexecuting but the other failing.

One example of a spread instrument is a calendar spread instrument. Thelegs of a calendar spread instrument differ in delivery date of theunderlier. The leg with the earlier occurring delivery date is oftenreferred to as the lead month contract. A leg with a later occurringdelivery date is often referred to as a deferred month contract. Anotherexample of a spread instrument is a butterfly spread instrument, whichincludes three legs having different delivery dates. The delivery datesof the legs may be equidistant to each other. The counterparty ordersthat are matched against such a combination order may be individual,“outright” orders or may be part of other combination orders.

In other words, an exchange may receive, and hold or let rest on thebooks, outright orders for individual contracts as well as outrightorders for spreads associated with the individual contracts. An outrightorder (for either a contract or for a spread) may include an outrightbid or an outright offer, although some outright orders may bundle manybids or offers into one message (often called a mass quote).

A spread is an order for the price difference between two contracts.This results in the trader holding a long and a short position in two ormore related futures or options on futures contracts, with the objectiveof profiting from a change in the price relationship. A typical spreadproduct includes multiple legs, each of which may include one or moreunderlying financial instruments. A butterfly spread product, forexample, may include three legs. The first leg may consist of buying afirst contract. The second leg may consist of selling two of a secondcontract. The third leg may consist of buying a third contract. Theprice of a butterfly spread product may be calculated as:Butterfly=Leg1−2×Leg2+Leg3.

In the above equation, Leg1 equals the price of the first contract, Leg2equals the price of the second contract and Leg3 equals the price of thethird contract. Thus, a butterfly spread could be assembled from twointer-delivery spreads in opposite directions with the center deliverymonth common to both spreads.

A calendar spread, also called an intra-commodity spread, for futures isan order for the simultaneous purchase and sale of the same futurescontract in different contract months (i.e., buying a September CME S&P500@ futures contract and selling a December CME S&P 500 futurescontract).

A crush spread is an order, usually in the soybean futures market, forthe simultaneous purchase of soybean futures and the sale of soybeanmeal and soybean oil futures to establish a processing margin. A crackspread is an order for a specific spread trade involving simultaneouslybuying and selling contracts in crude oil and one or more derivativeproducts, typically gasoline and heating oil. Oil refineries may trade acrack spread to hedge the price risk of their operations, whilespeculators attempt to profit from a change in the oil/gasoline pricedifferential.

A straddle is an order for the purchase or sale of an equal number ofputs and calls, with the same strike price and expiration dates. A longstraddle is a straddle in which a long position is taken in both a putand a call option. A short straddle is a straddle in which a shortposition is taken in both a put and a call option. A strangle is anorder for the purchase of a put and a call, in which the options havethe same expiration and the put strike is lower than the call strike,called a long strangle. A strangle may also be the sale of a put and acall, in which the options have the same expiration and the put strikeis lower than the call strike, called a short strangle. A pack is anorder for the simultaneous purchase or sale of an equally weighted,consecutive series of four futures contracts, quoted on an average netchange basis from the previous day's settlement price. Packs provide areadily available, widely accepted method for executing multiple futurescontracts with a single transaction. A bundle is an order for thesimultaneous sale or purchase of one each of a series of consecutivefutures contracts. Bundles provide a readily available, widely acceptedmethod for executing multiple futures contracts with a singletransaction.

Implication

Thus, an exchange may match outright orders, such as individualcontracts or spread orders (which as discussed herein could includemultiple individual contracts). The exchange may also imply orders fromoutright orders. For example, Exchange Computer System 100 may derive,identify and/or advertise, publish, display or otherwise make availablefor trading orders based on outright orders.

As was described above, the financial instruments which are the subjectof the orders to trade, may include one or more component financialinstruments. While each financial instrument may have its own orderbook, i.e. market, in which it may be traded, in the case of a financialinstrument having more than one component financial instrument, thosecomponent financial instruments may further have their own order booksin which they may be traded. Accordingly, when an order for a financialinstrument is received, it may be matched against a suitable counterorder in its own order book or, possibly, against a combination ofsuitable counter orders in the order books the component financialinstruments thereof, or which share a common component financialinstrument. For example, an order for a spread contract comprisingcomponent financial instruments A and B may be matched against anothersuitable order for that spread contract. However, it may also be matchedagainst suitable separate counter orders for the A and for the Bcomponent financial instruments found in the order books therefore.Similarly, if an order for the A contract is received and suitable matchcannot be found in the A order book, it may be possible to match orderfor A against a combination of a suitable counter order for a spreadcontract comprising the A and B component financial instruments and asuitable counter order for the B component financial instrument. This isreferred to as “implication” where a given order for a financialinstrument may be matched via a combination of suitable counter ordersfor financial instruments which share common, or otherwiseinterdependent, component financial instruments. Implication increasesthe liquidity of the market by providing additional opportunities fororders to be traded. Increasing the number of transactions may furtherincrease the number of transaction fees collected by the electronictrading system.

The order for a particular financial instrument actually received from amarket participant, whether it comprises one or more component financialinstruments, is referred to as a “real” or “outright” order, or simplyas an outright. The one or more orders which must be synthesized andsubmitted into order books other than the order book for the outrightorder in order to create matches therein, are referred to as “implied”orders. Upon receipt of an incoming order, the identification orderivation of suitable implied orders which would allow at least apartial trade of the incoming outright order to be executed is referredto as “implication” or “implied matching”, the identified orders beingreferred to as an “implied match.” Depending on the number of componentfinancial instruments involved, and whether those component financialinstruments further comprise component financial instruments of theirown, there may be numerous different implied matches identified whichwould allow the incoming order to be at least partially matched andmechanisms may be provided to arbitrate, e.g., automatically, amongthem, such as by picking the implied match comprising the least numberof component financial instruments or the least number of synthesizedorders.

Upon receipt of an incoming order, or thereafter, a combination of oneor more suitable/hypothetical counter orders which have not actuallybeen received but if they were received, would allow at least a partialtrade of the incoming order to be executed, may be, e.g., automatically,identified or derived and referred to as an “implied opportunity.” Aswith implied matches, there may be numerous implied opportunitiesidentified for a given incoming order. Implied opportunities areadvertised to the market participants, such as via suitable syntheticorders, e.g. counter to the desired order, being placed on therespective order books to rest (or give the appearance that there is anorder resting) and presented via the market data feed, electronicallycommunicated to the market participants, to appear available to trade inorder to solicit the desired orders from the market participants.Depending on the number of component financial instruments involved, andwhether those component financial instruments further comprise componentfinancial instruments of their own, there may be numerous impliedopportunities, the submission of a counter order in response thereto,would allow the incoming order to be at least partially matched.

Implied opportunities, e.g. the advertised synthetic orders, mayfrequently have better prices than the corresponding real orders in thesame contract. This can occur when two or more traders incrementallyimprove their order prices in the hope of attracting a trade, sincecombining the small improvements from two or more real orders can resultin a big improvement in their combination. In general, advertisingimplied opportunities at better prices will encourage traders to enterthe opposing orders to trade with them. The more implied opportunitiesthat the match engine of an electronic trading system cancalculate/derive, the greater this encouragement will be and the morethe exchange will benefit from increased transaction volume. However,identifying implied opportunities may be computationally intensive. In ahigh-performance trading system where low transaction latency isimportant, it may be important to identify and advertise impliedopportunities quickly so as to improve or maintain market participantinterest and/or market liquidity.

For example, two different outright orders may be resting on the booksor be available to trade or match. The orders may be resting becausethere are no outright orders that match the resting orders. Thus, eachof the orders may wait or rest on the books until an appropriateoutright counteroffer comes into the exchange or is placed by a user ofthe exchange. The orders may be for two different contracts that onlydiffer in delivery dates. It should be appreciated that such orderscould be represented as a calendar spread order. Instead of waiting fortwo appropriate outright orders to be placed that would match the twoexisting or resting orders, the Exchange Computer System may identify ahypothetical spread order that, if entered into the system as a tradablespread order, would allow the Exchange Computer System to match the twooutright orders. The exchange may thus advertise or make available aspread order to users of the exchange system that, if matched with atradable spread order, would allow the exchange to also match the tworesting orders. Thus, the match engine is configured to detect that thetwo resting orders may be combined into an order in the spreadinstrument and accordingly creates an implied order.

In other words, the exchange's matching system may imply thecounteroffer order by using multiple orders to create the counterofferorder. Examples of spreads include implied IN, implied OUT, 2nd- ormultiple-generation, crack spreads, straddle, strangle, butterfly, andpack spreads. Implied IN spread orders are derived from existingoutright orders in individual legs. Implied OUT outright orders arederived from a combination of an existing spread order and an existingoutright order in one of the individual underlying legs. Implied orderscan fill in gaps in the market and allow spreads and outright futurestraders to trade in a product where there would otherwise have beenlittle or no available bids and asks.

For example, implied IN spreads may be created from existing outrightorders in individual contracts where an outright order in a spread canbe matched with other outright orders in the spread or with acombination of orders in the legs of the spread. An implied OUT spreadmay be created from the combination of an existing outright order in aspread and an existing outright order in one of the individualunderlying leg. An implied IN or implied OUT spread may be created whenan electronic match system simultaneously works synthetic spread ordersin spread markets and synthetic orders in the individual leg marketswithout the risk to the trader/broker of being double filled or filledon one leg and not on the other leg.

By linking the spread and outright markets, implied spread tradingincreases market liquidity. For example, a buy in one contract month andan offer in another contract month in the same futures contract cancreate an implied market in the corresponding calendar spread. Anexchange may match an order for a spread product with another order forthe spread product. Some existing exchanges attempt to match orders forspread products with multiple orders for legs of the spread products.With such systems, every spread product contract is broken down into acollection of legs and an attempt is made to match orders for the legs.

Implied orders, unlike real orders, are generated by electronic tradingsystems. In other words, implied orders are computer generated ordersderived from real orders. The system creates the “derived” or “implied”order and provides the implied order as a market that may be tradedagainst. If a trader trades against this implied order, then the realorders that combined to create the implied order and the resultingmarket are executed as matched trades. Implied orders generally increaseoverall market liquidity. The creation of implied orders increases thenumber of tradable items, which has the potential of attractingadditional traders. Exchanges benefit from increased transaction volume.Transaction volume may also increase as the number of matched tradeitems increases.

Examples of implied spread trading include those disclosed in U.S.Patent Publication No. 2005/0203826, entitled “Implied Spread TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon. Examples of implied markets include thosedisclosed in U.S. Pat. No. 7,039,610, entitled “Implied Market TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon.

In some cases, the outright market for the deferred month or otherconstituent contract may not be sufficiently active to provide marketdata (e.g., bid-offer data) and/or trade data. Spread instrumentsinvolving such contracts may nonetheless be made available by theexchange. The market data from the spread instruments may then be usedto determine a settlement price for the constituent contract. Thesettlement price may be determined, for example, through a boundaryconstraint-based technique based on the market data (e.g., bid-offerdata) for the spread instrument, as described in U.S. Patent PublicationNo. 2015/0073962 entitled “Boundary Constraint-Based Settlement inSpread Markets” (“the '962 Publication”), the entire disclosure of whichis incorporated by reference herein and relied upon. Settlement pricedetermination techniques may be implemented to cover calendar monthspread instruments having different deferred month contracts.

Volatility Data Structures and Calculations

FIG. 3 depicts a flow chart 250 showing operation of the system 100 ofFIG. 1. In particular, FIG. 3 shows a computer implemented method forcombining dual volatility measurements on a graphical user interface(GUI) 222 of the display 214 of the computer system 200. As describedwith respect to the following embodiments the processor 202 of thecomputer system 200 may be referred to as a volatility controller 202.The volatility controller 202 performs specialized calculationsdescribed herein as well as rendering the GUI 222, processing andreceiving user inputs from the GUI 222, and implementing the dualvolatility display using the GUI 222. FIGS. 4-8 illustrate exampleembodiments of the GUI 222. Additional, different, or fewer acts may beincluded.

At act 252, the volatility controller 202, receives, via the GUI 222, auser selection for an anchor point. The anchor point may be a date. FIG.4 illustrates an example GUI 222 configured to receive the userselection at anchor point selector 300. The anchor point selector 300may include a slider 302 (slider mechanism) with an indicator thatslides along available anchor points such as different days. Other timegranularity may be used such as different times of day, differentmonths, or different years. In one example, only expiration dates foroptions (e.g., for a particular asset or for a particular Exchange) areavailable for selection on the anchor point selector 300. The anchorpoint selector 300 may include indicia for calendar dates or relativedays (e.g., today, yesterday, tomorrow, two days ago, etc.) listed ast_(−n) to t⁻¹ before the anchor date and from t₁ to t_(n) after theanchor date. The anchor point indicator 301 is a line that divideshistorical volatility values and implied volatility values according tothe setting of the anchor point selector 300. According to the movementof the anchor point selector 300, the relative location of the anchorpoint indicator 301 with respect to the volatility data changes.However, in this embodiment, the location of the anchor point indicator301 and/or a reference line 305 within the GUI may not change.

As an alternative to the slider 302 other user inputs may be used. Theuser input may be a date field, a pull down menu, a radial selector, ascroll bar, a dial, or another user input mechanism included in the GUI222.

The volatility controller 202 may define one or more initializationparameters for the GUI. The initialization parameters may include assetidentifiers, timing parameters, volatility parameters, or otherparameters.

The asset identifier identifies the asset for the dual volatilitymeasurements. Examples include any underlying product, security,commodity, equity, index, or interest rate product tradeable on theExchange Computer System 100. The asset identifier may identify a groupof assets (e.g., a portfolio, a basket of financial instruments, etc.),or an asset class (e.g., all assets meeting one or more criteria).

At act 254, the volatility controller 202 selects timing parameters suchas a time window including the anchor point. The volatility controller202 may retrieve a time window parameter from the memory 204. Exampletime window parameters may include a time window duration, a startingtime value, and an ending time value.

The time window parameters may be defined according to a userpreference, as asset identifier, or a market condition. The userpreference may be entered via the anchor point selector 300 to definethe time window duration, the starting time value, and/or the endingtime value. Alternatively, the time window duration may be tied to theasset. For example, the volatility controller 202 may access a lookuptable for the asset identifier to determine the time window duration.For example, different assets may have different expiration dates foroptions, which impacts the time window needed to provide meaningfulvolatility information. In another example, the time window duration maybe tied to a market condition. For example, the volatility controller202 may determine a market condition such as an inflation rate, aninterest rate, a volatility index, or another value to select the timewindow.

At act 256, the volatility controller 202 (e.g., historical volatilitymodule 142) calculates a set of past volatility values 303 based on thetime window and the anchor point. In some examples, the volatilitycontroller 202 calculates a global or complete set of past volatilityvalues 303 before receiving the initialization information for the GUI222. The set of past volatility values 303 are independent of anchordate. In other words, the volatility controller 202 stores the pastvolatility values 303 in a time series such as a list associated bydate. Subsequently, when rendering the GUI 222, the volatilitycontroller 202 access a subset of the list according to the anchor dateand the time window. The subset may be centered at the anchor date andhave a length equal to the time window. In other words, the volatilitycontroller 202 selects a subset of the table or matrix of all possiblevolatility values according to the anchor date and the time window forthe set of past volatility values 303.

At act 258, the volatility controller 202 (e.g., implied volatilitymodule 143) calculates a set of future volatility values 304 based onthe time window and the anchor point. The set of past volatility values303 and the set of future volatility values 304 are combined to generatea multi-dimensional table. The future volatility values 304 aredependent on anchor date. In other words, each anchor date has a set offuture volatility values 304 based on the current conditions of thepredicted or perceived asset prices at that time. Therefore, each anchordate is associated with a different set of future volatility values 304.The multi-dimensional table may represent this data by an array ofvalues for each anchor date for the future volatility values 304 and asingle dimensional vector associated with time for the past volatilityvalues 303, as shown by Table 1.

TABLE 1 Anchor Date Past Volatility Values 303 Future Volatility Values304 t⁻² P(t⁻⁶) P(t⁻⁵) P(t⁻⁴) P(t⁻³) P(t⁻²) F⁻²(t⁻¹) F⁻²(t₀) F⁻²(t₁)F⁻²(t₂) F⁻²(t₃) t⁻¹ P(t⁻⁵) P(t⁻⁴) P(t⁻³) P(t⁻²) P(t⁻¹) F⁻¹(t₀) F⁻¹(t₁)F⁻¹(t₂) F⁻¹(t₃) F⁻¹(t₄) t₀ P(t⁻⁴) P(t⁻³) P(t⁻²) P(t⁻¹) P(t₀) F₀(t₁)F₀(t₂) F₀(t₃) F₀(t₄) F₀(t₅) t₁ P(t⁻³) P(t⁻²) P(t⁻¹) P(t₀) P(t₁) F₁(t₂)F₁(t₃) F₁(t₄) F₁(t₅) F₁(t₆) t₂ P(t⁻²) P(t⁻¹) P(t₀) P(t₁) P(t₂) F₂(t₃)F₂(t₄) F₂(t₅) F₂(t₆) F₂(t₇)

Table 1 demonstrates that for transitioning from any given anchor date(e.g., −t₂) to another anchor date (e.g., −t₁), the past volatilityvalues 303 shift in time by the same increment as the anchor date.However, for the same transition in anchor date, the future volatilityvalues 304 may be completely different. That is, there may be no overlapbetween F⁻²(t) and F⁻¹(t). For example, the volatility controller 202shifts in time the set of past volatility values 303 in response to atransition from the first anchor point to the second anchor point basedon movement on the slider 302. The volatility controller 202 replacesthe set of future volatility values 304 with a replacement set of futurevolatility values in response to the transition from the first anchorpoint to the second anchor point on the slider 302.

The volatility controller 202 (e.g., volatility synthesis module 144)accesses multidimensional data from a row of Table 1 to synthesize anindex combining the historical volatility data 303 and the impliedvolatility data 304.

At act 260, generating a dual volatility display for the GUI 222including the set of past volatility values 303 and the set of futurevolatility values 304. The GUI 222 may include price values on they-axis for the magnitude of the volatility values and time values forthe x-axis. The volatility controller 202 selects volatility point datesin the time window in response to available transactions in the set ofpast volatility values 303 and the set of future volatility values 304.For example, Table 1 may define the availability of volatility pointdates. In addition or in the alternative, the available volatilitypoints dates may depend on options expiration dates or dates associatedwith the underlying financial instrument.

The dual volatility display for the GUI 222 may include dual volatilityplot or a continuous line connecting at least one of the set of pastvolatility values and at least one of the set of future volatilityvalues.

As the anchor date is changed, for example, by using slider 302, thevolatility controller 202 accesses different rows of Table 1. Inpractice, the combined index changes differently on the past volatilityside than on the future volatility side as the slider 302 is moved. Onthe past volatility side, the past volatility values 303 appear to slideinto reference line 305, but the shape does not change. The pastvolatility values 303 are translated to the right as the slider 302 ismoved forward in time and to the left as the slider 302 is movedbackward in time. When the slider 302 is moved forward in time updatedvalues are added to the right side of the graph and when the slider 302is moved backward in time update values are added to the left side ofthe graph. Conversely, on the future volatility side, when the slider302 is moved, completely new values are used on the right side ofreference line 305. The future volatility side of the graph may appearto jump around quickly. The change in the future volatility values 304demonstrate the changes in implied volatility based on conditions in theoptions markets on the anchor date.

As the slider 302 is moved, the data for the set of past volatilityvalues 303 and the set of future volatility values 304 and the timevalues for the x-axis changes. However, the location on the GUI 222 ofthe reference line 305 does not change. In effect, the slider 302animates the set of past volatility values 303 and the set of futurevolatility values 304 to show the passage of time.

Thus, the slider 302 is moved from a first position corresponding to afirst anchor point to a second (or subsequent) position of the slidermechanism corresponding to a second anchor point to change bot the setof past volatility values 303 and the set of future volatility values304. Specifically, the set of past volatility values 303 are shifted intime in response to a transition from the first anchor point to thesecond anchor point and the set of future volatility values 304 arereplaced with a replacement set of future volatility values in responseto the transition from the first anchor point to the second anchorpoint.

In other words, the acts of FIG. 3 may be repeated such that second andsubsequent dual volatility displays for the GUI 222 are generated. TheGUI 222 is configured to receive a second user selection for a secondanchor point. The volatility controller 202 selects a second time windowincluding the second anchor point. The historical volatility module 142calculates a second set of past volatility values based on the secondtime window and the second anchor point. The implied volatility module143 calculates a second set of future volatility values based on thesecond time window and the second anchor point. The volatilitycontroller 202 generates the second dual volatility display for the GUI222 including the second set of past volatility values and the secondset of future volatility values.

FIG. 5 depicts another example GUI 222 for dual volatility calculationsincluding forward volatility. The GUI 222 may include a forwardvolatility range 310 for the time period leading up to an expirationdate of the options used to derive the implied volatility or the set offuture volatility values 304. The time period may be a forwardvolatility region time duration selected according to the particularfinancial instrument, underlying asset, or corresponding expiry calendar(e.g., futures calendar or options calendar).

The forward volatility range 310 may be calculated from the impliedvolatility based on the volatility for future dates are averages overthe time interval leading up to those dates. More specifically, theforward volatility values may be calculated according to Equation 4:σ_(F)=√{square root over ((σ₂ ² T ₂−σ₁ ² T ₁)/(T ₂ −T ₁))}  Eq. 4

Using Equation 4, if there is a 6 month implied volatility (σ² ₁)=0.35,and 1 year implied volatility (σ² ₂)=0.45, then 6 month forward-impliedvolatility==Sqrt[(0.45²*1−0.35²*0.5)/(1−0.5)]==0.5315]. The forwardimplied volatility is effectively a square root of time-weighted averageof the two observable implied volatilities.

The volatility controller 202 is configured to calculate a forwardvolatility region time duration associated with the set of futurevolatility values 302 corresponding to the width of the forwardvolatility range 310 and a magnitude of the forward volatility valuescorresponding to the location along the y-axis of the forward volatilityrange 310. Further, the volatility controller 202 may adjust themagnitude of the forward volatility values and/or the forward volatilityregion time duration in response to user inputs from the slider 302.That is, the transition from the first anchor point to the second anchorpoint triggers and adjustment in the forward volatility range 310.

FIG. 6 depicts another example GUI 22 for dual volatility calculationsincluding a dynamic matrix 330. The matrix 330 numerically representingthe set of future volatility values 304. The matrix selector 333 is auser input for toggling between the matrix 330 and the dual volatilityplot of FIG. 4 or FIG. 5. The user may use the slider 300 to cyclethrough different dual volatility plots according to the anchor data.When a more detailed analysis or discrete numbers are desired, the userprovides an input to the matrix selector 333 to display the dynamicmatrix 330 including numeric representation of the set of futurevolatility values 304. The GUI 222 may include another matrix and matrixselector (not illustrated) for the set of past volatility values 303.

FIG. 7 depicts another example GUI 222 for dual volatility calculationsincluding multiple anchors. A first anchor 402 corresponds to a firstdual volatility plot 403 (illustrated by a solid line) and a secondanchor 404 corresponds to a second dual volatility plot 405 (illustratedby a dotted line). The GUI 222 may include multiple sliders or otherselectors for the first anchor 402 and the second anchor 404. The firstanchor selector 406 may receive inputs for an anchor point for the firstanchor 402. The second anchor selector 407 may receive inputs for ananchor point for the second anchor 404.

The dual anchor selector 401 may be configured to receive inputs toactivate the second anchor 404 and the second anchor selector 407. Inaddition or in the alternative, the dual anchor selector 401 may triggerthe volatility controller 202 to generate a graphical indicator ofdifferences between the first dual volatility plot 403 and the seconddual volatility plot 405 displayed by the GUI 222.

The graphical indicator may include lines that connect correspondingdates in the first dual volatility plot 403 and the second dualvolatility plot 405. The graphical indicator may include encoded shadingbetween the first dual volatility plot 403 and the second dualvolatility plot 405 that represent the magnitude of the differencesbetween the first dual volatility plot 403 and the second dualvolatility plot 405. The shading may include grayscale, colors, or otherindicia that represent the differences.

Further, the GUI 222 may receive updated slider inputs for the secondanchor 404. The volatility controller 202 updates the graphicalindicator of differences between the first dual volatility plot 403 andthe second dual volatility plot 405 in response to the updated sliderinputs.

FIG. 8 depicts another example GUI 222 for dual volatility calculationsincluding a frequency selector 353. The frequency selector 353 receivesinputs that specify the frequency (tick size) of the time series in thedual volatility plot. Example frequencies for the time series in thedual volatility plot include hourly, daily, weekly, monthly or othertime periods. The frequency selector 353 may receive a first frequencysetting for the set of past volatility vales 403 and a second frequencysetting for the set of implied volatility values 404. The firstfrequency setting may be different from the second frequency setting.FIG. 8 illustrates where the second frequency setting is smaller thanthe first frequency setting.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the invention or of what may beclaimed, but rather as descriptions of features specific to particularembodiments of the invention. Certain features that are described inthis specification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable sub-combination. Moreover, although features may be describedas acting in certain combinations and even initially claimed as such,one or more features from a claimed combination can in some cases beexcised from the combination, and the claimed combination may bedirected to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings and describedherein in a particular order, this should not be understood as requiringthat such operations be performed in the particular order shown or insequential order, or that all illustrated operations be performed, toachieve desirable results. In certain circumstances, multitasking andparallel processing may be advantageous. Moreover, the separation ofvarious system components in the described embodiments should not beunderstood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be usedto interpret or limit the scope or meaning of the claims. In addition,in the foregoing Detailed Description, various features may be groupedtogether or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

It is therefore intended that the foregoing detailed description beregarded as illustrative rather than limiting, and that it be understoodthat it is the following claims, including all equivalents, that areintended to define the spirit and scope of this invention.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. Many otherembodiments may be apparent to those of skill in the art upon reviewingthe disclosure. Other embodiments may be utilized and derived from thedisclosure, such that structural and logical substitutions and changesmay be made without departing from the scope of the disclosure.Additionally, the illustrations are merely representational and may notbe drawn to scale. Certain proportions within the illustrations may beexaggerated, while other proportions may be minimized. Accordingly, thedisclosure and the figures are to be regarded as illustrative ratherthan restrictive.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the invention or of what may beclaimed, but rather as descriptions of features specific to particularembodiments of the invention. Certain features that are described inthis specification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable sub-combination. Moreover, although features may be describedabove as acting in certain combinations and even initially claimed assuch, one or more features from a claimed combination can in some casesbe excised from the combination, and the claimed combination may bedirected to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings and describedherein in a particular order, this should not be understood as requiringthat such operations be performed in the particular order shown or insequential order, or that all illustrated operations be performed, toachieve desirable results. In certain circumstances, multitasking andparallel processing may be advantageous. Moreover, the separation ofvarious system components in the embodiments described above should notbe understood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be usedto interpret or limit the scope or meaning of the claims. In addition,in the foregoing Detailed Description, various features may be groupedtogether or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

It is therefore intended that the foregoing detailed description beregarded as illustrative rather than limiting, and that it be understoodthat it is the following claims, including all equivalents, that areintended to define the spirit and scope of this invention.

What is claimed is:
 1. A method comprising: receiving a first timedesignation; selecting a time window including the first timedesignation; selecting at least one realized historic volatility valuefrom before the first time designation; calculating at least one futurevolatility value from after the first time designation; generating adual volatility display including the at least one realized historicvolatility value and the at least one future volatility value; andreceiving a second time designation from a user input, the second timedesignation corresponding to at least one additional realized historicvolatility value or at least one additional future volatility value,wherein the second time designation pivots the dual volatility displayto separate the at least one additional realized historic volatilityvalue and the at least one future volatility value, which dynamicallyadjusts the calculations of volatility in real time under the control ofthe user input.
 2. The method of claim 1, further comprising: displayingthe dual volatility display at a graphical user interface (GUI).
 3. Themethod of claim 1, further comprising: selecting the at least onerealized historic volatility in response to available transactions. 4.The method of claim 1, wherein the dual volatility display includes acontinuous line connecting the at least one realized historic volatilityvalue and the at least one future volatility value.
 5. The method ofclaim 1, wherein the dual volatility display includes a slider mechanismfor the user input.
 6. The method of claim 5, wherein the first timedesignation corresponds to a first position of the slider mechanism, andthe second time designation corresponds to a second position of theslider mechanism.
 7. The method of claim 6, further comprising: shiftingin time the at least one realized historic volatility value in responseto a transition from the first position to the second position of theslider mechanism.
 8. The method of claim 7, further comprising:replacing the at least one future volatility value with one or morereplacement future volatility values in response to the transition fromthe first position to the second position of the slider mechanism. 9.The method of claim 7, further comprising: calculating a forwardvolatility region time duration associated with the at least one futurevolatility value; and adjusting the forward volatility region timeduration in response to the transition from the first position to thesecond position.
 10. The method of claim 1, wherein the dual volatilitydisplay includes a matrix for numerically representing the at least onerealized historic volatility value and the at least one futurevolatility value.
 11. The method of claim 10, further comprising:generating a graphical indicator of differences between the dualvolatility display using the first time designation and the dualvolatility display using the second time designation.
 12. An apparatuscomprising: a user input configured to receive a user selection for afirst time designation; and a processor configured to select at leastone realized historic volatility value from before the first timedesignation and at least one future volatility value for after the timedesignation and generate a dual volatility display including the atleast one realized historic volatility value and the at least one futurevolatility value, wherein the user input receives a second timedesignation corresponding to at least one additional realized historicvolatility value or at least one additional future volatility value,wherein the second time designation pivots the dual volatility displayto separate the at least one additional realized historic volatilityvalue and the at least one future volatility value, which dynamicallyadjusts the calculations of volatility in real time under the control ofthe user input.
 13. The apparatus of claim 12, future comprising: adisplay configured to generate a plot for the dual volatility displayincluding the at least one realized historic volatility value and the atleast one future volatility value.
 14. The apparatus of claim 13,wherein the plot includes a continuation line connecting the at leastone realized historic volatility value and the at least one futurevolatility value.
 15. The apparatus of claim 12, wherein the user inputis a slider mechanism.
 16. The apparatus of claim 15, wherein the firsttime designation corresponds to a position of the slider mechanism. 17.The apparatus of claim 15, wherein the at least one past volatilityvalue is shifted in time in response to a change in position of theslider mechanism.
 18. A non-transitory computer readable mediumincluding instructions that when executed by a processor are configuredto perform: receive a first time designation; select a time windowincluding the first time designation; select at least one realizedhistoric volatility value from before the first time designation;calculate at least one future volatility value for after the timedesignation; generate a dual volatility display including the at leastone realized historic volatility value and the at least one futurevolatility value; and receive a second time designation from a userinput, the second time designation corresponding to at least oneadditional realized historic volatility value or at least one additionalfuture volatility value, wherein the second time designation pivots thedual volatility display to separate the at least one additional realizedhistoric volatility value and the at least one future volatility value,which dynamically adjusts the calculations of volatility in real timeunder the control of the user input.
 19. The non-transitory computerreadable medium of claim 18, wherein the dual volatility displayincludes a continuous line connecting the at least one realized historicvolatility value and the at least one future volatility value.